Table of Contents

• Deep Statistical SolversBalthazar Donon, Zhengying Liu, Wenzhuo Liu, Isabelle Guyon, Antoine Marot, Marc Schoenauer. [doi]
• Sample complexity and effective dimension for regression on manifoldsAndrew D. McRae, Justin Romberg, Mark A. Davenport. [doi]
• Federated Accelerated Stochastic Gradient DescentHonglin Yuan, Tengyu Ma. [doi]
• GAN Memory with No ForgettingYulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin. [doi]
• Investigating Gender Bias in Language Models Using Causal Mediation AnalysisJesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, Stuart M. Shieber. [doi]
• Minimax Bounds for Generalized Linear ModelsKuan-Yun Lee, Thomas A. Courtade. [doi]
• Meta-NeighborhoodsSiyuan Shan, Yang Li, Junier B. Oliva. [doi]
• Reasoning about Uncertainties in Discrete-Time Dynamical Systems using Polynomial FormsSriram Sankaranarayanan 0001, Yi Chou, Eric Goubault, Sylvie Putot. [doi]
• Domain Generalization via Entropy RegularizationShanshan Zhao, Mingming Gong, Tongliang Liu, Huan Fu, Dacheng Tao. [doi]
• Automatically Learning Compact Quality-aware Surrogates for Optimization ProblemsKai Wang 0040, Bryan Wilder, Andrew Perrault, Milind Tambe. [doi]
• Is normalization indispensable for training deep neural network?Jie Shao, Kai Hu, Changhu Wang, Xiangyang Xue, Bhiksha Raj. [doi]
• Debugging Tests for Model ExplanationsJulius Adebayo, Michael Muelly, Ilaria Liccardi, Been Kim. [doi]
• Variational Bayesian Monte Carlo with Noisy LikelihoodsLuigi Acerbi. [doi]
• Estimation of Skill Distribution from a TournamentAli Jadbabaie, Anuran Makur, Devavrat Shah. [doi]
• Neuronal Gaussian Process RegressionJohannes Friedrich. [doi]
• Adversarial robustness via robust low rank representationsPranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan. [doi]
• Synthesizing Tasks for Block-based ProgrammingUmair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, Adish Singla. [doi]
• Generalized Hindsight for Reinforcement LearningAlexander C. Li, Lerrel Pinto, Pieter Abbeel. [doi]
• The Pitfalls of Simplicity Bias in Neural NetworksHarshay Shah, Kaustav Tamuly, Aditi Raghunathan, Prateek Jain 0002, Praneeth Netrapalli. [doi]
• Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational AutoencodersMasha Itkina, Boris Ivanovic, Ransalu Senanayake, Mykel J. Kochenderfer, Marco Pavone. [doi]
• Adversarially Robust Few-Shot Learning: A Meta-Learning ApproachMicah Goldblum, Liam Fowl, Tom Goldstein. [doi]
• Handling Missing Data with Graph Representation LearningJiaxuan You, Xiaobai Ma, Daisy Yi Ding, Mykel J. Kochenderfer, Jure Leskovec. [doi]
• Belief Propagation Neural NetworksJonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon. [doi]
• Identifying signal and noise structure in neural population activity with Gaussian process factor modelsStephen L. Keeley, Mikio Aoi, Yiyi Yu, Spencer L. Smith, Jonathan W. Pillow. [doi]
• Denoised Smoothing: A Provable Defense for Pretrained ClassifiersHadi Salman, Mingjie Sun, Greg Yang, Ashish Kapoor, J. Zico Kolter. [doi]
• Semi-Supervised Partial Label Learning via Confidence-Rated Margin MaximizationWei Wang, Min-Ling Zhang. [doi]
• Hyperparameter Ensembles for Robustness and Uncertainty QuantificationFlorian Wenzel, Jasper Snoek, Dustin Tran, Rodolphe Jenatton. [doi]
• Online Structured Meta-learningHuaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong. [doi]
• PLLay: Efficient Topological Layer based on Persistent LandscapesKwangho Kim, Jisu Kim, Manzil Zaheer, Joon Sik Kim, Frédéric Chazal, Larry A. Wasserman. [doi]
• Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clusteringMeng Liu, David F. Gleich. [doi]
• Approximation Based Variance Reduction for Reparameterization GradientsTomas Geffner, Justin Domke. [doi]
• Learning efficient task-dependent representations with synaptic plasticityColin Bredenberg, Eero P. Simoncelli, Cristina Savin. [doi]
• How do fair decisions fare in long-term qualification?Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang 0001, Cheng Zhang 0005. [doi]
• Field-wise Learning for Multi-field Categorical DataZhibin Li 0002, Jian Zhang 0002, Yongshun Gong, Yazhou Yao, Qiang Wu 0001. [doi]
• Improving Policy-Constrained Kidney Exchange via Pre-ScreeningDuncan C. McElfresh, Michael J. Curry, Tuomas Sandholm, John Dickerson 0001. [doi]
• On the Power of Louvain in the Stochastic Block ModelVincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn, David Saulpic. [doi]
• Learning Some Popular Gaussian Graphical Models without Condition Number BoundsJonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra. [doi]
• Adversarial Self-Supervised Contrastive LearningMinseon Kim, Jihoon Tack, Sung Ju Hwang. [doi]
• Compositional Generalization via Neural-Symbolic Stack MachinesXinyun Chen, Chen Liang, Adams Wei Yu, Dawn Song, Denny Zhou. [doi]
• Global Convergence and Variance Reduction for a Class of Nonconvex-Nonconcave Minimax ProblemsJunchi Yang, Negar Kiyavash, Niao He. [doi]
• Triple descent and the two kinds of overfitting: where & why do they appear?Stéphane d'Ascoli, Levent Sagun, Giulio Biroli. [doi]
• Unfolding the Alternating Optimization for Blind Super ResolutionZhengxiong Luo, Yan Huang 0008, Shang Li, Liang Wang, Tieniu Tan. [doi]
• Self-supervised Co-Training for Video Representation LearningTengda Han, Weidi Xie, Andrew Zisserman. [doi]
• Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONASHan Shi, Renjie Pi, Hang Xu, Zhenguo Li, James T. Kwok, Tong Zhang. [doi]
• Finite-Time Analysis for Double Q-learningHuaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang. [doi]
• Bayesian Attention ModulesXinjie Fan, Shujian Zhang, Bo Chen 0001, Mingyuan Zhou. [doi]
• The Implications of Local Correlation on Learning Some Deep FunctionsEran Malach, Shai Shalev-Shwartz. [doi]
• Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation LearningLuca Oneto, Michele Donini, Giulia Luise, Carlo Ciliberto, Andreas Maurer, Massimiliano Pontil. [doi]
• The Diversified Ensemble Neural NetworkShaofeng Zhang, Meng Liu, Junchi Yan. [doi]
• Empirical Likelihood for Contextual BanditsNikos Karampatziakis, John Langford 0001, Paul Mineiro. [doi]
• Every View Counts: Cross-View Consistency in 3D Object Detection with Hybrid-Cylindrical-Spherical VoxelizationQi Chen, Lin Sun, Ernest Cheung, Alan L. Yuille. [doi]
• Bayesian Probabilistic Numerical Integration with Tree-Based ModelsHarrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth Flaxman, François-Xavier Briol. [doi]
• SnapBoost: A Heterogeneous Boosting MachineThomas P. Parnell, Andreea Anghel, Malgorzata Lazuka, Nikolas Ioannou, Sebastian Kurella, Peshal Agarwal, Nikolaos Papandreou, Haralampos Pozidis. [doi]
• Learning Global Transparent Models consistent with Local Contrastive ExplanationsTejaswini Pedapati, Avinash Balakrishnan, Karthikeyan Shanmugam, Amit Dhurandhar. [doi]
• No-Regret Learning and Mixed Nash Equilibria: They Do Not MixEmmanouil-Vasileios Vlatakis-Gkaragkounis, Lampros Flokas, Thanasis Lianeas, Panayotis Mertikopoulos, Georgios Piliouras. [doi]
• Robust large-margin learning in hyperbolic spaceMelanie Weber 0001, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar. [doi]
• Probably Approximately Correct Constrained LearningLuiz F. O. Chamon, Alejandro Ribeiro. [doi]
• Improving Generalization in Reinforcement Learning with Mixture RegularizationKaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng. [doi]
• Optimal Learning from Verified Training DataNick Bishop, Long Tran-Thanh, Enrico Gerding. [doi]
• Exploiting weakly supervised visual patterns to learn from partial annotationsKaustav Kundu, Joseph Tighe. [doi]
• Learnability with Indirect Supervision SignalsKaifu Wang, Qiang Ning, Dan Roth. [doi]
• Uncertainty-Aware Learning for Zero-Shot Semantic SegmentationPing Hu, Stan Sclaroff, Kate Saenko. [doi]
• Implicit Distributional Reinforcement LearningYuguang Yue, Zhendong Wang, Mingyuan Zhou. [doi]
• Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize ScalingYu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos. [doi]
• MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy ModelsSourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun. [doi]
• Heavy-tailed Representations, Text Polarity Classification & Data AugmentationHamid Jalalzai, Pierre Colombo, Chloé Clavel, Éric Gaussier, Giovanna Varni, Emmanuel Vignon, Anne Sabourin. [doi]
• Deeply Learned Spectral Total Variation DecompositionTamara G. Grossmann, Yury Korolev, Guy Gilboa, Carola B. Schönlieb. [doi]
• Subgroup-based Rank-1 Lattice Quasi-Monte CarloYueming Lyu, Yuan Yuan 0002, Ivor W. Tsang. [doi]
• Towards Safe Policy Improvement for Non-Stationary MDPsYash Chandak, Scott M. Jordan, Georgios Theocharous, Martha White, Philip S. Thomas. [doi]
• Zero-Resource Knowledge-Grounded Dialogue GenerationLinxiao Li, Can Xu, Wei Wu 0014, Yufan Zhao, Xueliang Zhao, Chongyang Tao. [doi]
• Model-based Adversarial Meta-Reinforcement LearningZichuan Lin, Garrett Thomas, Guangwen Yang, Tengyu Ma. [doi]
• Noise-Contrastive Estimation for Multivariate Point ProcessesHongyuan Mei, Tom Wan, Jason Eisner. [doi]
• Learning to Detect Objects with a 1 Megapixel Event CameraEtienne Perot, Pierre de Tournemire, Davide Nitti 0002, Jonathan Masci, Amos Sironi. [doi]
• Provably Efficient Reinforcement Learning with Kernel and Neural Function ApproximationsZhuoran Yang, Chi Jin, Zhaoran Wang, Mengdi Wang, Michael I. Jordan. [doi]
• Off-Policy Evaluation and Learning for External Validity under a Covariate ShiftMasatoshi Uehara, Masahiro Kato, Shota Yasui. [doi]
• Rotation-Invariant Local-to-Global Representation Learning for 3D Point CloudSeohyun Kim, Jaeyoo Park, Bohyung Han. [doi]
• Graph Meta Learning via Local SubgraphsKexin Huang, Marinka Zitnik. [doi]
• Adam with Bandit Sampling for Deep LearningRui Liu, Tianyi Wu, Barzan Mozafari. [doi]
• Learning Manifold Implicitly via Explicit Heat-Kernel LearningYufan Zhou, Changyou Chen, Jinhui Xu 0001. [doi]
• Entropic Causal Inference: Identifiability and Finite Sample ResultsSpencer Compton, Murat Kocaoglu, Kristjan H. Greenewald, Dmitriy Katz. [doi]
• Learning by Minimizing the Sum of Ranked RangeShu Hu, Yiming Ying, Xin Wang 0045, Siwei Lyu. [doi]
• GANSpace: Discovering Interpretable GAN ControlsErik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, Sylvain Paris. [doi]
• Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistencyRobert Geirhos, Kristof Meding, Felix A. Wichmann. [doi]
• Robust Sequence Submodular MaximizationGamal Sallam, Zizhan Zheng, Jie Wu 0001, Bo Ji. [doi]
• Parametric Instance Classification for Unsupervised Visual Feature learningYue Cao 0001, Zhenda Xie, Bin Liu 0035, Yutong Lin, Zheng Zhang 0022, Han Hu 0004. [doi]
• MOPO: Model-based Offline Policy OptimizationTianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Y. Zou, Sergey Levine, Chelsea Finn, Tengyu Ma. [doi]
• StratLearner: Learning a Strategy for Misinformation Prevention in Social NetworksGuangmo Tong. [doi]
• Estimating decision tree learnability with polylogarithmic sample complexityGuy Blanc, Neha Gupta 0002, Jane Lange, Li-Yang Tan. [doi]
• Generalization bound of globally optimal non-convex neural network training: Transportation map estimation by infinite dimensional Langevin dynamicsTaiji Suzuki. [doi]
• Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised LearningTao Han, Junyu Gao, Yuan Yuan 0001, Qi Wang 0009. [doi]
• Heuristic Domain AdaptationShuhao Cui, Xuan Jin, Shuhui Wang, Yuan He, Qingming Huang. [doi]
• Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication TimeJerry Li 0001, Guanghao Ye. [doi]
• Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?Vitaly Kurin, Saad Godil, Shimon Whiteson, Bryan Catanzaro. [doi]
• Automatic Perturbation Analysis for Scalable Certified Robustness and BeyondKaidi Xu, Zhouxing Shi, Huan Zhang 0001, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh. [doi]
• Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph CompletionZhanqiu Zhang, Jianyu Cai, Jie Wang 0005. [doi]
• Uncertainty Quantification for Inferring Hawkes NetworksHaoyun Wang, Liyan Xie, Alex Cuozzo, Simon Mak, Yao Xie 0002. [doi]
• Marginal Utility for Planning in Continuous or Large Discrete Action SpacesZaheen Farraz Ahmad, Levi Lelis, Michael Bowling. [doi]
• Pointer Graph NetworksPetar Velickovic, Lars Buesing, Matthew C. Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell. [doi]
• Synthesize, Execute and Debug: Learning to Repair for Neural Program SynthesisKavi Gupta, Peter Ebert Christensen, Xinyun Chen, Dawn Song. [doi]
• Online Convex Optimization Over Erdos-Renyi Random NetworksJinlong Lei, Peng Yi, Yiguang Hong, Jie Chen, Guodong Shi. [doi]
• Modeling Shared responses in Neuroimaging Studies through MultiView ICAHugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin. [doi]
• Unsupervised Text Generation by Learning from SearchJingjing Li, Zichao Li, Lili Mou, Xin Jiang, Michael R. Lyu, Irwin King. [doi]
• How hard is to distinguish graphs with graph neural networks?Andreas Loukas. [doi]
• Neural Networks Fail to Learn Periodic Functions and How to Fix ItZiyin Liu, Tilman Hartwig, Masahito Ueda. [doi]
• First-Order Methods for Large-Scale Market Equilibrium ComputationYuan Gao, Christian Kroer. [doi]
• Margins are Insufficient for Explaining Gradient BoostingAllan Grønlund, Lior Kamma, Kasper Green Larsen. [doi]
• Deep Archimedean CopulasChun Kai Ling, Fei Fang, J. Zico Kolter. [doi]
• A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine LearningBhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Jize Zhang, Yi Zhou, Timo Bremer. [doi]
• Estimation and Imputation in Probabilistic Principal Component Analysis with Missing Not At Random DataAude Sportisse, Claire Boyer, Julie Josse. [doi]
• Security Analysis of Safe and Seldonian Reinforcement Learning AlgorithmsPinar Ozisik, Philip S. Thomas. [doi]
• PRANK: motion Prediction based on RANKingYuriy Biktairov, Maxim Stebelev, Irina Rudenko, Oleh Shliazhko, Boris Yangel. [doi]
• A new inference approach for training shallow and deep generalized linear models of noisy interacting neuronsGabriel Mahuas, Giulio Isacchini, Olivier Marre, Ulisse Ferrari, Thierry Mora. [doi]
• Self-Supervised MultiModal Versatile NetworksJean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelovic, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman. [doi]
• Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case RatesKaiwen Zhou, Anthony Man-Cho So, James Cheng. [doi]
• A Topological Filter for Learning with Label NoisePengxiang Wu, Songzhu Zheng, Mayank Goswami 0001, Dimitris N. Metaxas, Chao Chen 0012. [doi]
• Theory-Inspired Path-Regularized Differential Network Architecture SearchPan Zhou, Caiming Xiong, Richard Socher, Steven Chu Hong Hoi. [doi]
• Sliding Window Algorithms for k-Clustering ProblemsMichele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitskii, Morteza Zadimoghaddam. [doi]
• FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPsAlekh Agarwal, Sham M. Kakade, Akshay Krishnamurthy, Wen Sun. [doi]
• Self-training Avoids Using Spurious Features Under Domain ShiftYining Chen, Colin Wei, Ananya Kumar, Tengyu Ma. [doi]
• A Simple and Efficient Smoothing Method for Faster Optimization and Local ExplorationKevin Scaman, Ludovic Dos Santos, Merwan Barlier, Igor Colin. [doi]
• Bayes Consistency vs. H-Consistency: The Interplay between Surrogate Loss Functions and the Scoring Function ClassMingyuan Zhang, Shivani Agarwal 0001. [doi]
• Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective FunctionLingkai Kong, Molei Tao. [doi]
• Adversarial Soft Advantage Fitting: Imitation Learning without Policy OptimizationPaul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai. [doi]
• Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability VolumesJuan Luis Gonzalez Bello, Munchurl Kim. [doi]
• Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-SolversKiwon Um, Robert Brand, Yun (Raymond) Fei, Philipp Holl, Nils Thuerey. [doi]
• CompRess: Self-Supervised Learning by Compressing RepresentationsSoroush Abbasi Koohpayegani, Ajinkya Tejankar, Hamed Pirsiavash. [doi]
• Neural Complexity MeasuresYoonho Lee, Juho Lee, Sung Ju Hwang, Eunho Yang, Seungjin Choi. [doi]
• Learning Black-Box Attackers with Transferable Priors and Query FeedbackJiancheng Yang, Yangzhou Jiang, Xiaoyang Huang, Bingbing Ni, Chenglong Zhao. [doi]
• Do Adversarially Robust ImageNet Models Transfer Better?Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry. [doi]
• Strictly Batch Imitation Learning by Energy-based Distribution MatchingDaniel Jarrett, Ioana Bica, Mihaela van der Schaar. [doi]
• Influence-Augmented Online Planning for Complex EnvironmentsJinke He, Miguel Suau, Frans A. Oliehoek. [doi]
• What Neural Networks Memorize and Why: Discovering the Long Tail via Influence EstimationVitaly Feldman, Chiyuan Zhang. [doi]
• Hierarchical Neural Architecture Search for Deep Stereo MatchingXuelian Cheng, Yiran Zhong, Mehrtash Harandi, Yuchao Dai, Xiaojun Chang, Hongdong Li, Tom Drummond, ZongYuan Ge. [doi]
• Incorporating Interpretable Output Constraints in Bayesian Neural NetworksWanqian Yang, Lars Lorch, Moritz A. Graule, Himabindu Lakkaraju, Finale Doshi-Velez. [doi]
• Correlation Robust Influence MaximizationLouis Chen, Divya Padmanabhan, Chee Chin Lim, Karthik Natarajan. [doi]
• Probabilistic Orientation Estimation with Matrix Fisher DistributionsDavid Mohlin, Josephine Sullivan, Gérald Bianchi. [doi]
• Adversarial Robustness of Supervised Sparse CodingJeremias Sulam, Ramchandran Muthukumar, Raman Arora. [doi]
• Multi-Stage Influence FunctionHongge Chen, Si Si, Yang Li 0058, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh. [doi]
• Hausdorff Dimension, Heavy Tails, and Generalization in Neural NetworksUmut Simsekli, Ozan Sener, George Deligiannidis, Murat A. Erdogdu. [doi]
• Effective Diversity in Population Based Reinforcement LearningJack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts. [doi]
• Deep reconstruction of strange attractors from time seriesWilliam Gilpin. [doi]
• Sub-sampling for Efficient Non-Parametric Bandit ExplorationDorian Baudry, Emilie Kaufmann, Odalric-Ambrym Maillard. [doi]
• Robust Multi-Agent Reinforcement Learning with Model UncertaintyKaiqing Zhang, Tao Sun, Yunzhe Tao, Sahika Genc, Sunil Mallya, Tamer Basar. [doi]
• Minibatch Stochastic Approximate Proximal Point MethodsHilal Asi, Karan Chadha, Gary Cheng, John C. Duchi. [doi]
• Neural Mesh Flow: 3D Manifold Mesh Generation via Diffeomorphic FlowsKunal Gupta, Manmohan Chandraker. [doi]
• From Boltzmann Machines to Neural Networks and Back AgainSurbhi Goel, Adam R. Klivans, Frederic Koehler. [doi]
• Is Long Horizon RL More Difficult Than Short Horizon RL?Ruosong Wang, Simon S. Du, Lin F. Yang, Sham M. Kakade. [doi]
• High-Dimensional Bayesian Optimization via Nested Riemannian ManifoldsNoémie Jaquier, Leonel Dario Rozo. [doi]
• Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear FunctionQuoc Tran-Dinh, Deyi Liu, Lam Nguyen. [doi]
• Distributionally Robust Parametric Maximum Likelihood EstimationViet Anh Nguyen, Xuhui Zhang, José H. Blanchet, Angelos Georghiou. [doi]
• How to Characterize The Landscape of Overparameterized Convolutional Neural NetworksYihong Gu, Weizhong Zhang, Cong Fang, Jason D. Lee, Tong Zhang 0001. [doi]
• Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic OptimalityKwang-Sung Jun, Chicheng Zhang. [doi]
• Sufficient dimension reduction for classification using principal optimal transport directionCheng Meng, Jun Yu, Jingyi Zhang, Ping Ma, Wenxuan Zhong. [doi]
• DynaBERT: Dynamic BERT with Adaptive Width and DepthLu Hou, Zhiqi Huang, Lifeng Shang, Xin Jiang, Xiao Chen, Qun Liu. [doi]
• Towards Better Generalization of Adaptive Gradient MethodsYingxue Zhou, Belhal Karimi, Jinxing Yu, Zhiqiang Xu, Ping Li 0001. [doi]
• Learning identifiable and interpretable latent models of high-dimensional neural activity using pi-VAEDing Zhou, Xue-Xin Wei. [doi]
• Bayesian Robust Optimization for Imitation LearningDaniel S. Brown, Scott Niekum, Marek Petrik. [doi]
• Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in RegretYingjie Fei, Zhuoran Yang, Yudong Chen, Zhaoran Wang, Qiaomin Xie. [doi]
• Identifying Learning Rules From Neural Network ObservablesAran Nayebi, Sanjana Srivastava, Surya Ganguli, Daniel L. Yamins. [doi]
• Certified Monotonic Neural NetworksXingchao Liu, Xing Han, Na Zhang, Qiang Liu 0001. [doi]
• Memory Based Trajectory-conditioned Policies for Learning from Sparse RewardsYijie Guo, Jongwook Choi, Marcin Moczulski, Shengyu Feng, Samy Bengio, Mohammad Norouzi 0002, Honglak Lee. [doi]
• Towards Playing Full MOBA Games with Deep Reinforcement LearningDeheng Ye, Guibin Chen, Wen Zhang, Sheng Chen, Bo Yuan, Bo Liu, Jia Chen, Zhao Liu, Fuhao Qiu, Hongsheng Yu, Yinyuting Yin, Bei Shi, Liang Wang, Tengfei Shi, Qiang Fu, Wei Yang, Lanxiao Huang, Wei Liu. [doi]
• Experimental design for MRI by greedy policy searchTim Bakker, Herke van Hoof, Max Welling. [doi]
• Bayesian Bits: Unifying Quantization and PruningMart van Baalen, Christos Louizos, Markus Nagel, Rana Ali Amjad, Ying Wang, Tijmen Blankevoort, Max Welling. [doi]
• RANet: Region Attention Network for Semantic SegmentationDingguo Shen, Yuanfeng Ji, Ping Li, Yi Wang, Di Lin. [doi]
• Fast Transformers with Clustered AttentionApoorv Vyas, Angelos Katharopoulos, François Fleuret. [doi]
• Overfitting Can Be Harmless for Basis Pursuit, But Only to a DegreePeizhong Ju, Xiaojun Lin, Jia Liu 0002. [doi]
• Dialog without Dialog Data: Learning Visual Dialog Agents from VQA DataMichael Cogswell, Jiasen Lu, Rishabh Jain, Stefan Lee, Devi Parikh, Dhruv Batra. [doi]
• Graph Policy Network for Transferable Active Learning on GraphsShengding Hu, Zheng Xiong, Meng Qu, Xingdi Yuan, Marc-Alexandre Côté, Zhiyuan Liu 0001, Jian Tang. [doi]
• 3D Shape Reconstruction from Vision and TouchEdward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal. [doi]
• Shared Space Transfer Learning for analyzing multi-site fMRI dataMuhammad Yousefnezhad, Alessandro Selvitella, Daoqiang Zhang, Andrew J. Greenshaw, Russell Greiner. [doi]
• Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier CertificatesWenhao Luo, Wen Sun, Ashish Kapoor. [doi]
• Leverage the Average: an Analysis of KL Regularization in Reinforcement LearningNino Vieillard, Tadashi Kozuno, Bruno Scherrer, Olivier Pietquin, Rémi Munos, Matthieu Geist. [doi]
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and ConfidenceKihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li. [doi]
• A Statistical Framework for Low-bitwidth Training of Deep Neural NetworksJianfei Chen, Yu Gai, Zhewei Yao, Michael W. Mahoney, Joseph E. Gonzalez. [doi]
• An analytic theory of shallow networks dynamics for hinge loss classificationFranco Pellegrini, Giulio Biroli. [doi]
• Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image PerturbationsJoel Dapello, Tiago Marques, Martin Schrimpf, Franziska Geiger, David D. Cox, James J. DiCarlo. [doi]
• Self-Supervised Learning by Cross-Modal Audio-Video ClusteringHumam Alwassel, Dhruv Mahajan 0001, Bruno Korbar, Lorenzo Torresani, Bernard Ghanem, Du Tran. [doi]
• GramGAN: Deep 3D Texture Synthesis From 2D ExemplarsTiziano Portenier, Siavash Arjomand Bigdeli, Orcun Goksel. [doi]
• A novel variational form of the Schatten-$p$ quasi-normParis Giampouras, René Vidal, Athanasios A. Rontogiannis, Benjamin D. Haeffele. [doi]
• Parameterized Explainer for Graph Neural NetworkDongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, Xiang Zhang 0001. [doi]
• CaSPR: Learning Canonical Spatiotemporal Point Cloud RepresentationsDavis Rempe, Tolga Birdal, Yongheng Zhao, Zan Gojcic, Srinath Sridhar 0002, Leonidas J. Guibas. [doi]
• Projection Robust Wasserstein Distance and Riemannian OptimizationTianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan. [doi]
• Improved Schemes for Episodic Memory-based Lifelong LearningYunhui Guo, Mingrui Liu, Tianbao Yang, Tajana Rosing. [doi]
• Spin-Weighted Spherical CNNsCarlos Esteves, Ameesh Makadia, Kostas Daniilidis. [doi]
• Pruning Filter in FilterFanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo, Guangming Lu, Xing Sun. [doi]
• First Order Constrained Optimization in Policy SpaceYiming Zhang 0010, Quan Vuong, Keith W. Ross. [doi]
• On the Stability and Convergence of Robust Adversarial Reinforcement Learning: A Case Study on Linear Quadratic SystemsKaiqing Zhang, Bin Hu, Tamer Basar. [doi]
• Learning Linear Programs from Optimal DecisionsYingcong Tan, Daria Terekhov, Andrew Delong. [doi]
• Stage-wise Conservative Linear BanditsAhmadreza Moradipari, Christos Thrampoulidis, Mahnoosh Alizadeh. [doi]
• Estimating weighted areas under the ROC curveAndreas Maurer, Massimiliano Pontil. [doi]
• Graph Stochastic Neural Networks for Semi-supervised LearningHaibo Wang, Chuan Zhou 0001, Xin Chen, Jia Wu 0001, Shirui Pan, Jilong Wang. [doi]
• Kernel Based Progressive Distillation for Adder Neural NetworksYixing Xu, Chang Xu 0002, Xinghao Chen 0001, Wei Zhang, Chunjing Xu, Yunhe Wang. [doi]
• Learning Individually Inferred Communication for Multi-Agent CooperationZiluo Ding, Tiejun Huang, Zongqing Lu. [doi]
• Implicit Rank-Minimizing AutoencoderLi Jing, Jure Zbontar, Yann LeCun. [doi]
• Towards Interpretable Natural Language Understanding with Explanations as Latent VariablesWangchunshu Zhou, Jinyi Hu, Hanlin Zhang, Xiaodan Liang, Maosong Sun, Chenyan Xiong, Jian Tang. [doi]
• Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization ProblemsSongtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong. [doi]
• Ensemble Distillation for Robust Model Fusion in Federated LearningTao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi. [doi]
• Woodbury Transformations for Deep Generative FlowsYou Lu 0003, Bert Huang. [doi]
• Rethinking Importance Weighting for Deep Learning under Distribution ShiftTongtong Fang, Nan Lu, Gang Niu 0001, Masashi Sugiyama. [doi]
• Estimating Training Data Influence by Tracing Gradient DescentGarima Pruthi, Frederick Liu, Satyen Kale, Mukund Sundararajan. [doi]
• 3D Self-Supervised Methods for Medical ImagingAiham Taleb, Winfried Loetzsch, Noel Danz, Julius Severin, Thomas Gaertner, Benjamin Bergner, Christoph Lippert. [doi]
• Reciprocal Adversarial Learning via Characteristic FunctionsShengxi Li, Zeyang Yu, Min Xiang, Danilo P. Mandic. [doi]
• Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimizationBenjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová. [doi]
• Regularizing Towards Permutation Invariance In Recurrent ModelsEdo Cohen-Karlik, Avichai Ben David, Amir Globerson. [doi]
• A General Method for Robust Learning from BatchesAyush Jain, Alon Orlitsky. [doi]
• Improving Auto-Augment via Augmentation-Wise Weight SharingKeyu Tian, Chen Lin, Ming Sun, Luping Zhou, Junjie Yan, Wanli Ouyang. [doi]
• Bridging Imagination and Reality for Model-Based Deep Reinforcement LearningGuangxiang Zhu, Minghao Zhang, Honglak Lee, Chongjie Zhang. [doi]
• HiPPO: Recurrent Memory with Optimal Polynomial ProjectionsAlbert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré. [doi]
• Learning outside the Black-Box: The pursuit of interpretable modelsJonathan Crabbé, Yao Zhang, William R. Zame, Mihaela van der Schaar. [doi]
• No-regret Learning in Price Competitions under Consumer Reference EffectsNegin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang. [doi]
• ShapeFlow: Learnable Deformation Flows Among 3D ShapesChiyu Max Jiang, Jingwei Huang, Andrea Tagliasacchi, Leonidas J. Guibas. [doi]
• Geo-PIFu: Geometry and Pixel Aligned Implicit Functions for Single-view Human ReconstructionTong He, John P. Collomosse, Hailin Jin, Stefano Soatto. [doi]
• Coresets for Regressions with Panel DataLingxiao Huang, K. Sudhir, Nisheeth K. Vishnoi. [doi]
• Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and ControlGiorgos Mamakoukas, Orest Xherija, Todd Murphey. [doi]
• Unsupervised Learning of Object Landmarks via Self-Training CorrespondenceDimitrios Mallis, Enrique Sanchez, Matthew Bell, Georgios Tzimiropoulos. [doi]
• Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural ProcessesAndrew Y. K. Foong, Wessel Bruinsma, Jonathan Gordon 0003, Yann Dubois, James Requeima, Richard E. Turner. [doi]
• Contextual Games: Multi-Agent Learning with Side InformationPier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause 0001, Maryam Kamgarpour. [doi]
• Learning Disentangled Representations and Group Structure of Dynamical EnvironmentsRobin Quessard, Thomas D. Barrett, William R. Clements. [doi]
• Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage DecompositionZihan Zhang, Yuan Zhou 0007, Xiangyang Ji. [doi]
• Value-driven Hindsight ModellingArthur Guez, Fabio Viola, Theophane Weber, Lars Buesing, Steven Kapturowski, Doina Precup, David Silver, Nicolas Heess. [doi]
• Variational Policy Gradient Method for Reinforcement Learning with General UtilitiesJunyu Zhang, Alec Koppel, Amrit Singh Bedi, Csaba Szepesvári, Mengdi Wang. [doi]
• Large-Scale Adversarial Training for Vision-and-Language Representation LearningZhe Gan, Yen-Chun Chen 0001, Linjie Li, Chen Zhu, Yu Cheng 0001, Jingjing Liu 0001. [doi]
• Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for FreeHaotao Wang, Tianlong Chen, Shupeng Gui, Ting-Kuei Hu, Ji Liu 0002, Zhangyang Wang. [doi]
• Stochastic Optimization with Laggard Data PipelinesNaman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar, Cyril Zhang. [doi]
• Temporal Variability in Implicit Online LearningNicolò Campolongo, Francesco Orabona. [doi]
• Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution AlignmentBen Usman, Avneesh Sud, Nick Dufour, Kate Saenko. [doi]
• Learning Long-Term Dependencies in Irregularly-Sampled Time SeriesMathias Lechner, Ramin M. Hasani. [doi]
• Statistical and Topological Properties of Sliced Probability DivergencesKimia Nadjahi, Alain Durmus, Lénaïc Chizat, Soheil Kolouri, Shahin Shahrampour, Umut Simsekli. [doi]
• On the linearity of large non-linear models: when and why the tangent kernel is constantChaoyue Liu 0001, Libin Zhu, Mikhail Belkin. [doi]
• Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity LearningHuan Fu, Shunming Li, Rongfei Jia, Mingming Gong, Binqiang Zhao, Dacheng Tao. [doi]
• GCOMB: Learning Budget-constrained Combinatorial Algorithms over Billion-sized GraphsSahil Manchanda, Akash Mittal, Anuj Dhawan, Sourav Medya, Sayan Ranu, Ambuj Singh. [doi]
• A Benchmark for Systematic Generalization in Grounded Language UnderstandingLaura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, Brenden M. Lake. [doi]
• Deep Multimodal Fusion by Channel ExchangingYikai Wang, Wenbing Huang, Fuchun Sun, Tingyang Xu, Yu Rong, JunZhou Huang. [doi]
• Improving robustness against common corruptions by covariate shift adaptationSteffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann 0001, Wieland Brendel, Matthias Bethge. [doi]
• Robust-Adaptive Control of Linear Systems: beyond Quadratic CostsEdouard Leurent, Odalric-Ambrym Maillard, Denis V. Efimov. [doi]
• Adversarial Counterfactual Learning and Evaluation for Recommender SystemDa Xu, Chuanwei Ruan, Evren Körpeoglu, Sushant Kumar, Kannan Achan. [doi]
• Gradient Regularized V-Learning for Dynamic Treatment RegimesYao Zhang, Mihaela van der Schaar. [doi]
• Provably Consistent Partial-Label LearningLei Feng, Jiaqi Lv, Bo Han 0003, Miao Xu, Gang Niu 0001, Xin Geng, Bo An 0001, Masashi Sugiyama. [doi]
• Part-dependent Label Noise: Towards Instance-dependent Label NoiseXiaobo Xia, Tongliang Liu, Bo Han 0003, Nannan Wang, Mingming Gong, Haifeng Liu, Gang Niu 0001, Dacheng Tao, Masashi Sugiyama. [doi]
• Graphon Neural Networks and the Transferability of Graph Neural NetworksLuana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro. [doi]
• Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEsJianzhun Du, Joseph Futoma, Finale Doshi-Velez. [doi]
• Characterizing Optimal Mixed Policies: Where to Intervene and What to ObserveSanghack Lee, Elias Bareinboim. [doi]
• Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large GamesStephen McAleer, John B. Lanier, Roy Fox, Pierre Baldi. [doi]
• Path Sample-Analytic Gradient Estimators for Stochastic Binary NetworksAlexander Shekhovtsov, Viktor Yanush, Boris Flach. [doi]
• Random Reshuffling: Simple Analysis with Vast ImprovementsKonstantin Mishchenko, Ahmed Khaled Ragab Bayoumi, Peter Richtárik. [doi]
• TinyTL: Reduce Memory, Not Parameters for Efficient On-Device LearningHan Cai, Chuang Gan, Ligeng Zhu, Song Han 0003. [doi]
• Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional EntropiesItai Gat, Idan Schwartz, Alexander G. Schwing, Tamir Hazan. [doi]
• POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic AnalysisWeichao Mao, Kaiqing Zhang, Qiaomin Xie, Tamer Basar. [doi]
• GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural NetworkPrune Truong, Martin Danelljan, Luc Van Gool, Radu Timofte. [doi]
• All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimationJean Barbier, Nicolas Macris, Cynthia Rush. [doi]
• Hierarchical nucleation in deep neural networksDiego Doimo, Aldo Glielmo, Alessio Ansuini, Alessandro Laio. [doi]
• GPS-Net: Graph-based Photometric Stereo NetworkZhuokun Yao, Kun Li, Ying Fu, Haofeng Hu, Boxin Shi. [doi]
• Statistical Efficiency of Thompson Sampling for Combinatorial Semi-BanditsPierre Perrault, Etienne Boursier, Michal Valko, Vianney Perchet. [doi]
• A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies ReconstructionZiqi Ke, Haris Vikalo. [doi]
• Model Interpretability through the lens of Computational ComplexityPablo Barceló, Mikaël Monet, Jorge Pérez 0001, Bernardo Subercaseaux. [doi]
• BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed BanditsMo Tiwari, Martin Jinye Zhang, James Mayclin, Sebastian Thrun, Chris Piech, Ilan Shomorony. [doi]
• High-Dimensional Sparse Linear BanditsBotao Hao, Tor Lattimore, Mengdi Wang. [doi]
• Improved Techniques for Training Score-Based Generative ModelsYang Song 0011, Stefano Ermon. [doi]
• Instance Selection for GANsTerrance Devries, Michal Drozdzal, Graham W. Taylor. [doi]
• COPT: Coordinated Optimal Transport on GraphsYihe Dong, Will Sawin. [doi]
• On the equivalence of molecular graph convolution and molecular wave function with poor basis setMasashi Tsubaki, Teruyasu Mizoguchi. [doi]
• Chaos, Extremism and Optimism: Volume Analysis of Learning in GamesYun Kuen Cheung, Georgios Piliouras. [doi]
• Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient TrackingIsidoros Tziotis, Constantine Caramanis, Aryan Mokhtari. [doi]
• The Hateful Memes Challenge: Detecting Hate Speech in Multimodal MemesDouwe Kiela, Hamed Firooz, Aravind Mohan, Vedanuj Goswami, Amanpreet Singh, Pratik Ringshia, Davide Testuggine. [doi]
• Generalized BoostingArun Sai Suggala, Bingbin Liu, Pradeep Ravikumar. [doi]
• Kernel Methods Through the Roof: Handling Billions of Points EfficientlyGiacomo Meanti, Luigi Carratino, Lorenzo Rosasco, Alessandro Rudi. [doi]
• Applications of Common Entropy for Causal InferenceMurat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath. [doi]
• Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep LearningPan Zhou, Jiashi Feng, Chao Ma 0012, Caiming Xiong, Steven Chu Hong Hoi, Weinan E. [doi]
• Prophet Attention: Predicting Attention with Future AttentionFenglin Liu, Xuancheng Ren, Xian Wu, Shen Ge, Wei Fan 0001, Yuexian Zou, Xu Sun 0001. [doi]
• Exchangeable Neural ODE for Set ModelingYang Li 0012, Haidong Yi, Christopher M. Bender, Siyuan Shan, Junier B. Oliva. [doi]
• Feature Importance Ranking for Deep LearningMaksymilian Wojtas, Ke Chen 0001. [doi]
• Factor Graph Neural NetworksZhen Zhang, Fan Wu, Wee Sun Lee. [doi]
• A new convergent variant of Q-learning with linear function approximationDiogo Carvalho, Francisco S. Melo, Pedro Santos 0001. [doi]
• Inference for Batched BanditsKelly W. Zhang, Lucas Janson, Susan A. Murphy. [doi]
• PIE-NET: Parametric Inference of Point Cloud EdgesXiaogang Wang 0005, Yuelang Xu, Kai Xu 0004, Andrea Tagliasacchi, Bin Zhou, Ali Mahdavi-Amiri, Hao Zhang 0002. [doi]
• Making Non-Stochastic Control (Almost) as Easy as StochasticMax Simchowitz. [doi]
• Object Goal Navigation using Goal-Oriented Semantic ExplorationDevendra Singh Chaplot, Dhiraj Gandhi, Abhinav Gupta 0001, Russ R. Salakhutdinov. [doi]
• Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying KernelsYi Zhou, Chenglei Wu, Zimo Li, Chen Cao, Yuting Ye, Jason M. Saragih, Hao Li, Yaser Sheikh. [doi]
• Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample ComplexityKaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang. [doi]
• Neural Unsigned Distance Fields for Implicit Function LearningJulian Chibane, Aymen Mir, Gerard Pons-Moll. [doi]
• Online Sinkhorn: Optimal Transport distances from sample streamsArthur Mensch, Gabriel Peyré. [doi]
• Sampling-Decomposable Generative Adversarial RecommenderBinbin Jin, Defu Lian, Zheng Liu, Qi Liu 0003, Jianhui Ma, Xing Xie 0001, Enhong Chen. [doi]
• HM-ANN: Efficient Billion-Point Nearest Neighbor Search on Heterogeneous MemoryJie Ren 0015, Minjia Zhang, Dong Li. [doi]
• Online Multitask Learning with Long-Term MemoryMark Herbster, Stephen Pasteris, Lisa Tse. [doi]
• A Finite-Time Analysis of Two Time-Scale Actor-Critic MethodsYue Wu, Weitong Zhang, Pan Xu 0002, Quanquan Gu. [doi]
• Efficient Planning in Large MDPs with Weak Linear Function ApproximationRoshan Shariff, Csaba Szepesvári. [doi]
• Untangling tradeoffs between recurrence and self-attention in artificial neural networksGiancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie. [doi]
• Goal-directed Generation of Discrete Structures with Conditional Generative ModelsAmina Mollaysa, Brooks Paige, Alexandros Kalousis. [doi]
• Reinforcement Learning with Augmented DataMichael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas. [doi]
• Fast geometric learning with symbolic matricesJean Feydy, Joan Alexis Glaunès, Benjamin Charlier, Michael M. Bronstein. [doi]
• Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNsHao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu, Hao Su 0001. [doi]
• Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? - A Neural Tangent Kernel PerspectiveKaixuan Huang, Yuqing Wang, Molei Tao, Tuo Zhao. [doi]
• Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and SparsityDan Garber. [doi]
• Predictive Information Accelerates Learning in RLKuang-Huei Lee, Ian Fischer, Anthony Liu, Yijie Guo, Honglak Lee, John Canny, Sergio Guadarrama. [doi]
• Learning to Approximate a Bregman DivergenceAli Siahkamari, Xide Xia, Venkatesh Saligrama, David A. Castañón, Brian Kulis. [doi]
• The Surprising Simplicity of the Early-Time Learning Dynamics of Neural NetworksWei Hu, Lechao Xiao, Ben Adlam, Jeffrey Pennington. [doi]
• Auditing Differentially Private Machine Learning: How Private is Private SGD?Matthew Jagielski, Jonathan R. Ullman, Alina Oprea. [doi]
• Online Neural Connectivity Estimation with Noisy Group TestingAnne Draelos, John M. Pearson. [doi]
• Curriculum learning for multilevel budgeted combinatorial problemsAdel Nabli, Margarida Carvalho. [doi]
• Learning Agent Representations for Ice HockeyGuiliang Liu, Oliver Schulte, Pascal Poupart, Mike Rudd, Mehrsan Javan. [doi]
• Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable RecoursesKaivalya Rawal, Himabindu Lakkaraju. [doi]
• Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node EmbeddingsYu Chen 0022, Lingfei Wu, Mohammed J. Zaki. [doi]
• Implicit Neural Representations with Periodic Activation FunctionsVincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein. [doi]
• Task-Oriented Feature DistillationLinfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. [doi]
• Efficient Low Rank Gaussian Variational Inference for Neural NetworksMarcin Tomczak, Siddharth Swaroop, Richard E. Turner. [doi]
• TorsionNet: A Reinforcement Learning Approach to Sequential Conformer SearchTarun Gogineni, Ziping Xu, Exequiel Punzalan, Runxuan Jiang, Joshua Kammeraad, Ambuj Tewari, Paul Zimmerman. [doi]
• Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed FormHicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi. [doi]
• What Did You Think Would Happen? Explaining Agent Behaviour through Intended OutcomesHerman Yau, Chris Russell 0001, Simon Hadfield. [doi]
• Quantifying the Empirical Wasserstein Distance to a Set of Measures: Beating the Curse of DimensionalityNian Si, Jose H. Blanchet, Soumyadip Ghosh, Mark S. Squillante. [doi]
• Automatic Curriculum Learning through Value DisagreementYunzhi Zhang, Pieter Abbeel, Lerrel Pinto. [doi]
• Dynamic Submodular MaximizationMorteza Monemizadeh. [doi]
• A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game EncodingBruno Lecouat, Jean Ponce, Julien Mairal. [doi]
• MCUNet: Tiny Deep Learning on IoT DevicesJi Lin, Wei-Ming Chen, Yujun Lin, John Cohn, Chuang Gan, Song Han 0003. [doi]
• PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient LearningAlekh Agarwal, Mikael Henaff, Sham M. Kakade, Wen Sun. [doi]
• Robustness of Bayesian Neural Networks to Gradient-Based AttacksGinevra Carbone, Matthew Wicker, Luca Laurenti, Andrea Patané, Luca Bortolussi, Guido Sanguinetti. [doi]
• Efficient Clustering Based On A Unified View Of $K$-means And Ratio-cutShenfei Pei, Feiping Nie 0001, Rong Wang, Xuelong Li. [doi]
• SMYRF - Efficient Attention using Asymmetric ClusteringGiannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis. [doi]
• Online Robust Regression via SGD on the l1 lossScott Pesme, Nicolas Flammarion. [doi]
• Adaptation Properties Allow Identification of Optimized Neural CodesLuke I. Rast, Jan Drugowitsch. [doi]
• Almost Surely Stable Deep DynamicsNathan P. Lawrence, Philip D. Loewen, Michael G. Forbes, Johan U. Backström, R. Bhushan Gopaluni. [doi]
• Mitigating Forgetting in Online Continual Learning via Instance-Aware ParameterizationHung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei 0025, Min Sun. [doi]
• Multimodal Graph Networks for Compositional Generalization in Visual Question AnsweringRaeid Saqur, Karthik Narasimhan. [doi]
• Multi-task Additive Models for Robust Estimation and Automatic Structure DiscoveryYingjie Wang, Hong Chen, Feng Zheng, Chen Xu, Tieliang Gong, Yanhong Chen. [doi]
• Stable and expressive recurrent vision modelsDrew Linsley, Alekh Karkada Ashok, Lakshmi Narasimhan Govindarajan, Rex Liu, Thomas Serre. [doi]
• Self-Imitation Learning via Generalized Lower Bound Q-learningYunhao Tang. [doi]
• DeepSVG: A Hierarchical Generative Network for Vector Graphics AnimationAlexandre Carlier, Martin Danelljan, Alexandre Alahi, Radu Timofte. [doi]
• CryptoNAS: Private Inference on a ReLU BudgetZahra Ghodsi, Akshaj Kumar Veldanda, Brandon Reagen, Siddharth Garg. [doi]
• Residual Force Control for Agile Human Behavior Imitation and Extended Motion SynthesisYe Yuan 0007, Kris Kitani. [doi]
• Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local ElasticityShuxiao Chen, Hangfeng He, Weijie J. Su. [doi]
• Fourier Spectrum Discrepancies in Deep Network Generated ImagesTarik Dzanic, Karan Shah, Freddie D. Witherden. [doi]
• Predicting Training Time Without TrainingLuca Zancato, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto. [doi]
• Coresets for Near-Convex FunctionsMurad Tukan, Alaa Maalouf, Dan Feldman. [doi]
• Improved Algorithms for Convex-Concave Minimax OptimizationYuanhao Wang, Jian Li. [doi]
• Toward the Fundamental Limits of Imitation LearningNived Rajaraman, Lin F. Yang, Jiantao Jiao, Kannan Ramchandran. [doi]
• SGD with shuffling: optimal rates without component convexity and large epoch requirementsKwangjun Ahn, Chulhee Yun, Suvrit Sra. [doi]
• ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite PoolGellért Weisz, András György 0001, Wei-I Lin, Devon R. Graham, Kevin Leyton-Brown, Csaba Szepesvári, Brendan Lucier. [doi]
• Generative View Synthesis: From Single-view Semantics to Novel-view ImagesTewodros Amberbir Habtegebrial, Varun Jampani, Orazio Gallo, Didier Stricker. [doi]
• Online Decision Based Visual Tracking via Reinforcement LearningKe Song, Wei Zhang 0066, Ran Song, Yibin Li. [doi]
• Online MAP Inference of Determinantal Point ProcessesAditya Bhaskara, Amin Karbasi, Silvio Lattanzi, Morteza Zadimoghaddam. [doi]
• Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating PointBita Darvish Rouhani, Daniel Lo, Ritchie Zhao, Ming Liu, Jeremy Fowers, Kalin Ovtcharov, Anna Vinogradsky, Sarah Massengill, Lita Yang, Ray Bittner, Alessandro Forin, Haishan Zhu, Taesik Na, Prerak Patel, Shuai Che, Lok Chand Koppaka, Xia Song, Subhojit Som, Kaustav Das, Saurabh T., Steven K. Reinhardt, Sitaram Lanka, Eric S. Chung, Doug Burger. [doi]
• Interpretable and Personalized Apprenticeship Scheduling: Learning Interpretable Scheduling Policies from Heterogeneous User DemonstrationsRohan R. Paleja, Andrew Silva, Letian Chen, Matthew C. Gombolay. [doi]
• Weak Form Generalized Hamiltonian LearningKevin Course, Trefor W. Evans, Prasanth B. Nair. [doi]
• Pre-training via ParaphrasingMike Lewis, Marjan Ghazvininejad, Gargi Ghosh, Armen Aghajanyan, Sida Wang, Luke Zettlemoyer. [doi]
• Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection LaplacianYunpeng Shi, Shaohan Li, Gilad Lerman. [doi]
• On Uniform Convergence and Low-Norm Interpolation LearningLijia Zhou, D. J. Sutherland, Nati Srebro. [doi]
• Softmax Deep Double Deterministic Policy GradientsLing Pan, Qingpeng Cai, Longbo Huang. [doi]
• Low Distortion Block-Resampling with Spatially Stochastic NetworksSarah Jane Hong, Martín Arjovsky, Darryl Barnhart, Ian Thompson. [doi]
• A Non-Asymptotic Analysis for Stein Variational Gradient DescentAnna Korba, Adil Salim, Michael Arbel, Giulia Luise, Arthur Gretton. [doi]
• Deep Imitation Learning for Bimanual Robotic ManipulationFan Xie 0005, Alexander Chowdhury, M. Clara De Paolis Kaluza, Linfeng Zhao, Lawson L. S. Wong, Rose Yu. [doi]
• Community detection using fast low-cardinality semidefinite programming
Po-Wei Wang, J. Zico Kolter. [doi]
• Neural Dynamic Policies for End-to-End Sensorimotor LearningShikhar Bahl, Mustafa Mukadam, Abhinav Gupta 0001, Deepak Pathak. [doi]
• Finite Versus Infinite Neural Networks: an Empirical StudyJaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington, Ben Adlam, Lechao Xiao, Roman Novak, Jascha Sohl-Dickstein. [doi]
• Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative NetworksRandall Balestriero, Sebastien Paris, Richard G. Baraniuk. [doi]
• Subgraph Neural NetworksEmily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik. [doi]
• Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal TopologyQuynh Nguyen, Marco Mondelli. [doi]
• Learning Rich RankingsArjun Seshadri, Stephen Ragain, Johan Ugander. [doi]
• Reconsidering Generative Objectives For Counterfactual ReasoningDanni Lu, Chenyang Tao, Junya Chen, Fan Li, Feng Guo, Lawrence Carin. [doi]
• Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance AwarenessJeremiah Z. Liu, Zi Lin, Shreyas Padhy, Dustin Tran, Tania Bedrax-Weiss, Balaji Lakshminarayanan. [doi]
• Lightweight Generative Adversarial Networks for Text-Guided Image ManipulationBowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz. [doi]
• Noise2Same: Optimizing A Self-Supervised Bound for Image DenoisingYaochen Xie, Zhengyang Wang, Shuiwang Ji. [doi]
• Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement LearningMeng Zhou, Ziyu Liu, Pengwei Sui, Yixuan Li, Yuk Ying Chung. [doi]
• AutoBSS: An Efficient Algorithm for Block Stacking Style SearchYikang Zhang, Jian Zhang, Zhao Zhong. [doi]
• On the Expressiveness of Approximate Inference in Bayesian Neural NetworksAndrew Y. K. Foong, David R. Burt, Yingzhen Li, Richard E. Turner. [doi]
• Assessing SATNet's Ability to Solve the Symbol Grounding ProblemOscar Chang, Lampros Flokas, Hod Lipson, Michael Spranger. [doi]
• Robust compressed sensing using generative modelsAjil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis. [doi]
• Faster Wasserstein Distance Estimation with the Sinkhorn DivergenceLénaïc Chizat, Pierre Roussillon, Flavien Léger, François-Xavier Vialard, Gabriel Peyré. [doi]
• Wasserstein Distances for Stereo Disparity EstimationDivyansh Garg, Yan Wang 0051, Bharath Hariharan, Mark Campbell 0001, Kilian Q. Weinberger, Wei-Lun Chao. [doi]
• MESA: Boost Ensemble Imbalanced Learning with MEta-SAmplerZhining Liu 0002, Pengfei Wei, Jing Jiang 0002, Wei Cao, Jiang Bian 0002, Yi Chang 0001. [doi]
• Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved ConfoundingVictor Veitch, Anisha Zaveri. [doi]
• Coresets via Bilevel Optimization for Continual Learning and StreamingZalán Borsos, Mojmir Mutny, Andreas Krause 0001. [doi]
• Re-Examining Linear Embeddings for High-Dimensional Bayesian OptimizationBenjamin Letham, Roberto Calandra, Akshara Rai, Eytan Bakshy. [doi]
• Uncovering the Topology of Time-Varying fMRI Data using Cubical PersistenceBastian Rieck, Tristan Yates, Christian Bock, Karsten M. Borgwardt, Guy Wolf, Nicholas B. Turk-Browne, Smita Krishnaswamy. [doi]
• Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and BeyondGabriele Farina, Tuomas Sandholm. [doi]
• Hierarchical Quantized AutoencodersWill Williams, Sam Ringer, Tom Ash, David MacLeod, Jamie Dougherty, John Hughes. [doi]
• Proximity Operator of the Matrix Perspective Function and its ApplicationsJoong-Ho Won. [doi]
• Diverse Image Captioning with Context-Object Split Latent SpacesShweta Mahajan, Stefan Roth 0001. [doi]
• A kernel test for quasi-independenceTamara Fernandez, Wenkai Xu, Marc Ditzhaus, Arthur Gretton. [doi]
• Adapting to Misspecification in Contextual BanditsDylan J. Foster, Claudio Gentile, Mehryar Mohri, Julian Zimmert. [doi]
• Matrix Inference and Estimation in Multi-Layer ModelsParthe Pandit, Mojtaba Sahraee-Ardakan, Sundeep Rangan, Philip Schniter, Alyson K. Fletcher. [doi]
• Generative Neurosymbolic MachinesJindong Jiang, Sungjin Ahn. [doi]
• Latent World Models For Intrinsically Motivated ExplorationAleksandr Ermolov, Nicu Sebe. [doi]
• Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad SamplesSamarth Sinha, Zhengli Zhao, Anirudh Goyal, Colin Raffel, Augustus Odena. [doi]
• Model Selection in Contextual Stochastic Bandit ProblemsAldo Pacchiano, My Phan, Yasin Abbasi-Yadkori, Anup Rao 0002, Julian Zimmert, Tor Lattimore, Csaba Szepesvári. [doi]
• f-Divergence Variational InferenceNeng Wan, Dapeng Li, Naira Hovakimyan. [doi]
• Texture Interpolation for Probing Visual PerceptionJonathan Vacher, Aida Davila, Adam Kohn, Ruben Coen Cagli. [doi]
• Multi-label Contrastive Predictive CodingJiaming Song, Stefano Ermon. [doi]
• A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learningArnu Pretorius, Scott Cameron, Elan Van Biljon, Tom Makkink, Shahil Mawjee, Jeremy du Plessis, Jonathan Shock, Alexandre Laterre, Karim Beguir. [doi]
• Self-Supervised Relational Reasoning for Representation LearningMassimiliano Patacchiola, Amos J. Storkey. [doi]
• Neurosymbolic Transformers for Multi-Agent CommunicationJeevana Priya Inala, Yichen Yang 0008, James Paulos, Yewen Pu, Osbert Bastani, Vijay Kumar 0001, Martin Rinard, Armando Solar-Lezama. [doi]
• Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian ProcessesMengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao. [doi]
• What Do Neural Networks Learn When Trained With Random Labels?Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers. [doi]
• A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPsNevena Lazic, Dong Yin, Mehrdad Farajtabar, Nir Levine, Dilan Görür, Chris Harris, Dale Schuurmans. [doi]
• Learning to search efficiently for causally near-optimal treatmentsSamuel Håkansson, Viktor Lindblom, Omer Gottesman, Fredrik D. Johansson. [doi]
• UCSG-NET- Unsupervised Discovering of Constructive Solid Geometry TreeKacper Kania, Maciej Zieba, Tomasz Kajdanowicz. [doi]
• Conservative Q-Learning for Offline Reinforcement LearningAviral Kumar, Aurick Zhou, George Tucker, Sergey Levine. [doi]
• Efficient semidefinite-programming-based inference for binary and multi-class MRFsChirag Pabbaraju, Po-Wei Wang, J. Zico Kolter. [doi]
• Stochastic Deep Gaussian Processes over GraphsNaiqi Li, Wenjie Li, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia. [doi]
• On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome ThemChen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk. [doi]
• Consistent Structural Relation Learning for Zero-Shot SegmentationPeike Li, Yunchao Wei, Yi Yang 0001. [doi]
• Tree! I am no Tree! I am a low dimensional Hyperbolic EmbeddingRishi Sonthalia, Anna C. Gilbert. [doi]
• Differentiable Neural Architecture Search in Equivalent Space with Exploration EnhancementMiao Zhang, Huiqi Li, Shirui Pan, Xiaojun Chang, ZongYuan Ge, Steven W. Su. [doi]
• Learning from Positive and Unlabeled Data with Arbitrary Positive ShiftZayd Hammoudeh, Daniel Lowd. [doi]
• Human Parsing Based Texture Transfer from Single Image to 3D Human via Cross-View ConsistencyFang Zhao, ShengCai Liao, Kaihao Zhang, Ling Shao 0001. [doi]
• SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergenceSinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet. [doi]
• Decentralized Accelerated Proximal Gradient DescentHaishan Ye, Ziang Zhou, Luo Luo, Tong Zhang 0001. [doi]
• The Discrete Gaussian for Differential PrivacyClément L. Canonne, Gautam Kamath 0001, Thomas Steinke. [doi]
• Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksPatrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel 0001, Douwe Kiela. [doi]
• Self-Supervised Relationship ProbingJiuxiang Gu, Jason Kuen, Shafiq R. Joty, Jianfei Cai 0001, Vlad I. Morariu, Handong Zhao, Tong Sun. [doi]
• Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of DimensionalityYi Zhang, Orestis Plevrakis, Simon S. Du, Xingguo Li, Zhao Song 0002, Sanjeev Arora. [doi]
• Optimal and Practical Algorithms for Smooth and Strongly Convex Decentralized OptimizationDmitry Kovalev, Adil Salim, Peter Richtárik. [doi]
• Sinkhorn Natural Gradient for Generative ModelsZebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani. [doi]
• Limits to Depth Efficiencies of Self-AttentionYoav Levine, Noam Wies, Or Sharir, Hofit Bata, Amnon Shashua. [doi]
• Modeling and Optimization Trade-off in Meta-learningKatelyn Gao, Ozan Sener. [doi]
• Building powerful and equivariant graph neural networks with structural message-passingClément Vignac, Andreas Loukas, Pascal Frossard. [doi]
• UnModNet: Learning to Unwrap a Modulo Image for High Dynamic Range ImagingChu Zhou, Hang Zhao, Jin Han, Chang Xu 0002, Chao Xu 0006, Tiejun Huang, Boxin Shi. [doi]
• Online Linear Optimization with Many HintsAditya Bhaskara, Ashok Cutkosky, Ravi Kumar 0001, Manish Purohit. [doi]
• On Convergence of Nearest Neighbor Classifiers over Feature TransformationsLuka Rimanic, Cédric Renggli, Bo Li 0026, Ce Zhang. [doi]
• Network size and size of the weights in memorization with two-layers neural networksSébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer. [doi]
• A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max ProblemsJiawei Zhang, Peijun Xiao, Ruoyu Sun 0001, Zhi-Quan Luo. [doi]
• MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal AnglesZhennan Wang, Canqun Xiang, Wenbin Zou, Chen Xu 0004. [doi]
• Factorizable Graph Convolutional NetworksYiding Yang, Zunlei Feng, Mingli Song, Xinchao Wang. [doi]
• Provable Overlapping Community Detection in Weighted GraphsJimit Majmudar, Stephen A. Vavasis. [doi]
• Improving GAN Training with Probability Ratio Clipping and Sample ReweightingYue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu. [doi]
• PAC-Bayesian Bound for the Conditional Value at RiskZakaria Mhammedi, Benjamin Guedj, Robert C. Williamson. [doi]
• A Self-Tuning Actor-Critic AlgorithmTom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh. [doi]
• Provably adaptive reinforcement learning in metric spacesTongyi Cao, Akshay Krishnamurthy. [doi]
• f-GAIL: Learning f-Divergence for Generative Adversarial Imitation LearningXin Zhang, Yanhua Li, Ziming Zhang, Zhi-Li Zhang. [doi]
• Unsupervised Joint k-node Graph Representations with Compositional Energy-Based ModelsLeonardo Cotta, Carlos H. C. Teixeira, Ananthram Swami, Bruno Ribeiro 0001. [doi]
• Hierarchical Poset Decoding for Compositional Generalization in LanguageYinuo Guo, Zeqi Lin, Jian-Guang Lou, Dongmei Zhang. [doi]
• Supermasks in SuperpositionMitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi. [doi]
• Causal Discovery from Soft Interventions with Unknown Targets: Characterization and LearningAmin Jaber, Murat Kocaoglu, Karthikeyan Shanmugam, Elias Bareinboim. [doi]
• SIRI: Spatial Relation Induced Network For Spatial Description ResolutionPeiyao Wang, Weixin Luo, Yanyu Xu, Haojie Li, Shugong Xu, Jianyu Yang, Shenghua Gao. [doi]
• OTLDA: A Geometry-aware Optimal Transport Approach for Topic ModelingViet Huynh, He Zhao, Dinh Phung 0001. [doi]
• Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning ApproachAlireza Fallah 0001, Aryan Mokhtari, Asuman E. Ozdaglar. [doi]
• Reinforcement Learning in Factored MDPs: Oracle-Efficient Algorithms and Tighter Regret Bounds for the Non-Episodic SettingZiping Xu, Ambuj Tewari. [doi]
• A Discrete Variational Recurrent Topic Model without the Reparametrization TrickMehdi Rezaee, Francis Ferraro. [doi]
• Scalable Belief Propagation via Relaxed SchedulingVitalii Aksenov, Dan Alistarh, Janne H. Korhonen. [doi]
• Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networksZhou Fan, Zhichao Wang. [doi]
• Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and ControlYaofeng Desmond Zhong, Naomi Ehrich Leonard. [doi]
• Learning to Execute Programs with Instruction Pointer Attention Graph Neural NetworksDavid Bieber, Charles Sutton, Hugo Larochelle, Daniel Tarlow. [doi]
• Understanding spiking networks through convex optimizationAllan Mancoo, Sander W. Keemink, Christian K. Machens. [doi]
• RELATE: Physically Plausible Multi-Object Scene Synthesis Using Structured Latent SpacesSébastien Ehrhardt, Oliver Groth, Aron Monszpart, Martin Engelcke, Ingmar Posner, Niloy J. Mitra, Andrea Vedaldi. [doi]
• Boosting Adversarial Training with Hypersphere EmbeddingTianyu Pang, Xiao Yang, Yinpeng Dong, Taufik Xu, Jun Zhu 0001, Hang Su 0006. [doi]
• On the Value of Out-of-Distribution Testing: An Example of Goodhart's LawDamien Teney, Ehsan Abbasnejad, Kushal Kafle, Robik Shrestha, Christopher Kanan, Anton van den Hengel. [doi]
• Learning Augmented Energy Minimization via Speed ScalingÉtienne Bamas, Andreas Maggiori, Lars Rohwedder, Ola Svensson. [doi]
• Detecting Interactions from Neural Networks via Topological AnalysisZirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu. [doi]
• TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language GenerationChun-Hsing Lin, Siang-Ruei Wu, Hung-yi Lee, Yun-Nung Chen. [doi]
• Learning Restricted Boltzmann Machines with Sparse Latent VariablesGuy Bresler, Rares-Darius Buhai. [doi]
• Active Structure Learning of Causal DAGs via Directed Clique TreesChandler Squires, Sara Magliacane, Kristjan H. Greenewald, Dmitriy Katz, Murat Kocaoglu, Karthikeyan Shanmugam. [doi]
• Task-agnostic Exploration in Reinforcement LearningXuezhou Zhang, Yuzhe Ma, Adish Singla. [doi]
• Locally Differentially Private (Contextual) Bandits LearningKai Zheng 0007, Tianle Cai, Weiran Huang 0001, Zhenguo Li, Liwei Wang 0001. [doi]
• Dual-Resolution Correspondence NetworksXinghui Li, Kai Han, Shuda Li, Victor Prisacariu. [doi]
• Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image DeblurringJiangxin Dong, Stefan Roth 0001, Bernt Schiele. [doi]
• Calibrating CNNs for Lifelong LearningPravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai. [doi]
• MATE: Plugging in Model Awareness to Task Embedding for Meta LearningXiaohan Chen, Zhangyang Wang, Siyu Tang, Krikamol Muandet. [doi]
• RD$^2$: Reward Decomposition with Representation DecompositionZichuan Lin, Derek Yang, Li Zhao, Tao Qin, Guangwen Yang, Tie-Yan Liu. [doi]
• Self-Distillation as Instance-Specific Label SmoothingZhilu Zhang, Mert R. Sabuncu. [doi]
• Evaluating Attribution for Graph Neural NetworksBenjamin Sanchez-Lengeling, Jennifer N. Wei, Brian K. Lee, Emily Reif, Peter Wang, Wesley Wei Qian, Kevin McCloskey, Lucy J. Colwell, Alexander B. Wiltschko. [doi]
• ISTA-NAS: Efficient and Consistent Neural Architecture Search by Sparse CodingYibo Yang, Hongyang Li, Shan You, Fei Wang 0032, Chen Qian 0006, Zhouchen Lin. [doi]
• Learning Mutational SemanticsBrian Hie, Ellen D. Zhong, Bryan Bryson, Bonnie Berger. [doi]
• Effective Dimension Adaptive Sketching Methods for Faster Regularized Least-Squares OptimizationJonathan Lacotte, Mert Pilanci. [doi]
• Adversarial Crowdsourcing Through Robust Rank-One Matrix CompletionQianqian Ma, Alex Olshevsky. [doi]
• Robust Disentanglement of a Few Factors at a TimeBenjamin Estermann, Markus Marks, Mehmet Fatih Yanik. [doi]
• Sharper Generalization Bounds for Pairwise LearningYunwen Lei, Antoine Ledent, Marius Kloft. [doi]
• Efficient Algorithms for Device Placement of DNN Graph OperatorsJakub Tarnawski, Amar Phanishayee, Nikhil R. Devanur, Divya Mahajan, Fanny Nina Paravecino. [doi]
• Optimal Lottery Tickets via Subset Sum: Logarithmic Over-Parameterization is SufficientAnkit Pensia, Shashank Rajput, Alliot Nagle, Harit Vishwakarma, Dimitris S. Papailiopoulos. [doi]
• Video Object Segmentation with Adaptive Feature Bank and Uncertain-Region RefinementYongQing Liang, Xin Li, Navid Jafari, Jim Chen. [doi]
• Telescoping Density-Ratio EstimationBenjamin Rhodes, Kai Xu, Michael U. Gutmann. [doi]
• Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many ArmsMohsen Bayati, Nima Hamidi, Ramesh Johari, Khashayar Khosravi. [doi]
• GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private GeneratorsDingfan Chen, Tribhuvanesh Orekondy, Mario Fritz. [doi]
• Stochastic Stein DiscrepanciesJackson Gorham, Anant Raj, Lester Mackey. [doi]
• The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network VerificationChristian Tjandraatmadja, Ross Anderson, Joey Huchette, Will Ma, Krunal Patel, Juan Pablo Vielma. [doi]
• Preference-based Reinforcement Learning with Finite-Time GuaranteesYichong Xu, Ruosong Wang, Lin F. Yang, Aarti Singh, Artur Dubrawski. [doi]
• Recovery of sparse linear classifiers from mixture of responsesVenkata Gandikota, Arya Mazumdar, Soumyabrata Pal. [doi]
• Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals MeasurementXin Liu, Josh Fromm, Shwetak N. Patel, Daniel J. McDuff. [doi]
• Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable ModelAlex X. Lee, Anusha Nagabandi, Pieter Abbeel, Sergey Levine. [doi]
• Coherent Hierarchical Multi-Label Classification NetworksEleonora Giunchiglia, Thomas Lukasiewicz. [doi]
• Entrywise convergence of iterative methods for eigenproblemsVasileios Charisopoulos, Austin R. Benson, Anil Damle. [doi]
• Towards Learning Convolutions from ScratchBehnam Neyshabur. [doi]
• Neuron Merging: Compensating for Pruned NeuronsWoojeong Kim, Suhyun Kim, Mincheol Park, Geunseok Jeon. [doi]
• Reinforcement Learning for Control with Multiple FrequenciesJongmin Lee 0004, Byung-Jun Lee 0001, Kee-Eung Kim. [doi]
• Promoting Stochasticity for Expressive Policies via a Simple and Efficient Regularization MethodQi Zhou, Yufei Kuang, Zherui Qiu, Houqiang Li, Jie Wang 0005. [doi]
• On the Optimal Weighted $\ell_2$ Regularization in Overparameterized Linear RegressionDenny Wu, Ji Xu. [doi]
• Unsupervised Learning of Visual Features by Contrasting Cluster AssignmentsMathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, Armand Joulin. [doi]
• Online Matrix Completion with Side InformationMark Herbster, Stephen Pasteris, Lisa Tse. [doi]
• Bad Global Minima Exist and SGD Can Reach ThemShengchao Liu, Dimitris S. Papailiopoulos, Dimitris Achlioptas. [doi]
• Latent Bandits RevisitedJoey Hong, Branislav Kveton, Manzil Zaheer, Yinlam Chow, Amr Ahmed, Craig Boutilier. [doi]
• System Identification with Biophysical Constraints: A Circuit Model of the Inner RetinaCornelius Schröder, David Klindt, Sarah Strauß, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens. [doi]
• Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality ReductionBenoît Colange, Jaakko Peltonen, Michaël Aupetit, Denys Dutykh, Sylvain Lespinats. [doi]
• Batched Coarse Ranking in Multi-Armed BanditsNikolai Karpov, Qin Zhang 0001. [doi]
• Bayesian Optimization for Iterative LearningVu Nguyen, Sebastian Schulze, Michael A. Osborne. [doi]
• Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based AlgorithmsYingying Li, Na Li 0002. [doi]
• Gaussian Gated Linear NetworksDavid Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness. [doi]
• End-to-End Learning and Intervention in GamesJiayang Li, Jing Yu, Yu Marco Nie, Zhaoran Wang. [doi]
• A Measure-Theoretic Approach to Kernel Conditional Mean EmbeddingsJunhyung Park, Krikamol Muandet. [doi]
• Adversarial Distributional Training for Robust Deep LearningYinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu 0001, Hang Su 0006. [doi]
• Refactoring Policy for Compositional Generalizability using Self-Supervised Object ProposalsTongzhou Mu, Jiayuan Gu, Zhiwei Jia, Hao Tang, Hao Su 0001. [doi]
• Error Bounds of Imitating Policies and EnvironmentsTian Xu, Ziniu Li, Yang Yu. [doi]
• Efficient Exact Verification of Binarized Neural NetworksKai Jia, Martin Rinard. [doi]
• Reconciling Modern Deep Learning with Traditional Optimization Analyses: The Intrinsic Learning RateZhiyuan Li 0005, Kaifeng Lyu, Sanjeev Arora. [doi]
• Dual Instrumental Variable RegressionKrikamol Muandet, Arash Mehrjou, Si Kai Lee, Anant Raj. [doi]
• Predictive coding in balanced neural networks with noise, chaos and delaysJonathan Kadmon, Jonathan Timcheck, Surya Ganguli. [doi]
• Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast AlgorithmTianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan. [doi]
• Promoting Coordination through Policy Regularization in Multi-Agent Deep Reinforcement LearningJulien Roy, Paul Barde, Félix G. Harvey, Derek Nowrouzezahrai, Chris Pal. [doi]
• SDF-SRN: Learning Signed Distance 3D Object Reconstruction from Static ImagesChen-Hsuan Lin, Chaoyang Wang, Simon Lucey. [doi]
• Acceleration with a Ball Optimization OracleYair Carmon, Arun Jambulapati, Qijia Jiang, Yujia Jin, Yin Tat Lee, Aaron Sidford, Kevin Tian. [doi]
• Learning Kernel Tests Without Data SplittingJonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet. [doi]
• Fairness in Streaming Submodular Maximization: Algorithms and HardnessMarwa El Halabi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos, Jakub Tarnawski. [doi]
• Learning Implicit Functions for Topology-Varying Dense 3D Shape CorrespondenceFeng Liu, Xiaoming Liu. [doi]
• Functional Regularization for Representation Learning: A Unified Theoretical PerspectiveSiddhant Garg, Yingyu Liang. [doi]
• Distribution-free binary classification: prediction sets, confidence intervals and calibrationChirag Gupta, Aleksandr Podkopaev, Aaditya Ramdas. [doi]
• Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test ExamplesShafi Goldwasser, Adam Tauman Kalai, Yael Kalai, Omar Montasser. [doi]
• Kernel Alignment Risk Estimator: Risk Prediction from Training DataArthur Jacot, Berfin Simsek, Francesco Spadaro, Clément Hongler, Franck Gabriel. [doi]
• Exact Recovery of Mangled Clusters with Same-Cluster QueriesMarco Bressan 0002, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice. [doi]
• Synbols: Probing Learning Algorithms with Synthetic DatasetsAlexandre Lacoste, Pau Rodríguez López, Frederic Branchaud-Charron, Parmida Atighehchian, Massimo Caccia, Issam Hadj Laradji, Alexandre Drouin, Matt Craddock, Laurent Charlin, David Vázquez. [doi]
• Simplify and Robustify Negative Sampling for Implicit Collaborative FilteringJingtao Ding, Yuhan Quan, Quanming Yao, Yong Li 0008, Depeng Jin. [doi]
• Hardness of Learning Neural Networks with Natural WeightsAmit Daniely, Gal Vardi. [doi]
• Depth Uncertainty in Neural NetworksJavier Antorán, James Urquhart Allingham, José Miguel Hernández-Lobato. [doi]
• Geometric Exploration for Online ControlOrestis Plevrakis, Elad Hazan. [doi]
• Instance-based Generalization in Reinforcement LearningMartín Bertrán, Natalia Martínez, Mariano Phielipp, Guillermo Sapiro. [doi]
• NanoFlow: Scalable Normalizing Flows with Sublinear Parameter ComplexitySang Gil Lee, Sungwon Kim, Sungroh Yoon. [doi]
• Breaking the Communication-Privacy-Accuracy TrilemmaWei-Ning Chen, Peter Kairouz, Ayfer Özgür. [doi]
• Off-policy Policy Evaluation For Sequential Decisions Under Unobserved ConfoundingHongseok Namkoong, Ramtin Keramati, Steve Yadlowsky, Emma Brunskill. [doi]
• Limits on Testing Structural Changes in Ising ModelsAditya Gangrade, Bobak Nazer, Venkatesh Saligrama. [doi]
• Program Synthesis with Pragmatic CommunicationYewen Pu, Kevin Ellis, Marta Kryven, Josh Tenenbaum 0001, Armando Solar-Lezama. [doi]
• Large-Scale Methods for Distributionally Robust OptimizationDaniel Levy, Yair Carmon, John C. Duchi, Aaron Sidford. [doi]
• Fairness with Overlapping Groups; a Probabilistic PerspectiveForest Yang, Mouhamadou Cisse, Oluwasanmi Koyejo. [doi]
• Steady State Analysis of Episodic Reinforcement LearningBojun Huang. [doi]
• Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack TransferabilityNathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen. [doi]
• Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural NetworksSeyed Mohammadreza Mousavi Kalan, Zalan Fabian, Salman Avestimehr, Mahdi Soltanolkotabi. [doi]
• Learning Parities with Neural NetworksAmit Daniely, Eran Malach. [doi]
• Sample-Efficient Reinforcement Learning of Undercomplete POMDPsChi Jin, Sham M. Kakade, Akshay Krishnamurthy, Qinghua Liu. [doi]
• SLIP: Learning to predict in unknown dynamical systems with long-term memoryParia Rashidinejad, Jiantao Jiao, Stuart Russell. [doi]
• Learning to Play No-Press Diplomacy with Best Response Policy IterationThomas W. Anthony, Tom Eccles, Andrea Tacchetti, János Kramár, Ian M. Gemp, Thomas C. Hudson, Nicolas Porcel, Marc Lanctot, Julien Pérolat, Richard Everett 0001, Satinder Singh, Thore Graepel, Yoram Bachrach. [doi]
• Your Classifier can Secretly Suffice Multi-Source Domain AdaptationNaveen Venkat, Jogendra Nath Kundu, Durgesh Kumar Singh, Ambareesh Revanur, Venkatesh Babu R.. [doi]
• Non-Euclidean Universal ApproximationAnastasis Kratsios, Ievgen Bilokopytov. [doi]
• GRAF: Generative Radiance Fields for 3D-Aware Image SynthesisKatja Schwarz, Yiyi Liao, Michael Niemeyer, Andreas Geiger 0001. [doi]
• Geometric All-way Boolean Tensor DecompositionChanglin Wan, Wennan Chang, Tong Zhao, Sha Cao, Chi Zhang. [doi]
• Differentially Private Clustering: Tight Approximation RatiosBadih Ghazi, Ravi Kumar 0001, Pasin Manurangsi. [doi]
• On Infinite-Width HypernetworksEtai Littwin, Tomer Galanti, Lior Wolf, Greg Yang. [doi]
• Nimble: Lightweight and Parallel GPU Task Scheduling for Deep LearningWoosuk Kwon, Gyeong-In Yu, Eunji Jeong, Byung-Gon Chun. [doi]
• Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of DistributionsYi Hao, Alon Orlitsky. [doi]
• Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced DataUtkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee. [doi]
• Learning to Decode: Reinforcement Learning for Decoding of Sparse Graph-Based Channel CodesSalman Habib, Allison Beemer, Jörg Kliewer. [doi]
• Graph Random Neural Networks for Semi-Supervised Learning on GraphsWenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, Jie Tang 0001. [doi]
• Ode to an ODEKrzysztof Marcin Choromanski, Jared Quincy Davis, Valerii Likhosherstov, Xingyou Song, Jean-Jacques E. Slotine, Jacob Varley, Honglak Lee, Adrian Weller, Vikas Sindhwani. [doi]
• Non-reversible Gaussian processes for identifying latent dynamical structure in neural dataVirginia Rutten, Alberto Bernacchia, Maneesh Sahani, Guillaume Hennequin. [doi]
• Understanding and Exploring the Network with Stochastic ArchitecturesZhijie Deng, Yinpeng Dong, Shifeng Zhang, Jun Zhu 0001. [doi]
• Self-Adaptive Training: beyond Empirical Risk MinimizationLang Huang, Chao Zhang 0001, Hongyang Zhang 0001. [doi]
• On Correctness of Automatic Differentiation for Non-Differentiable FunctionsWonyeol Lee 0001, Hangyeol Yu, Xavier Rival, Hongseok Yang. [doi]
• Dual-Free Stochastic Decentralized Optimization with Variance ReductionHadrien Hendrikx, Francis R. Bach, Laurent Massoulié. [doi]
• Modular Meta-Learning with ShrinkageYutian Chen, Abram L. Friesen, Feryal Behbahani, Arnaud Doucet, David Budden, Matthew Hoffman 0002, Nando de Freitas. [doi]
• Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoderZhisheng Xiao, Qing Yan, Yali Amit. [doi]
• Tackling the Objective Inconsistency Problem in Heterogeneous Federated OptimizationJianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor. [doi]
• The MAGICAL Benchmark for Robust ImitationSam Toyer, Rohin Shah, Andrew Critch, Stuart Russell. [doi]
• Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and ReasoningWeili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar. [doi]
• Towards Convergence Rate Analysis of Random Forests for ClassificationWei Gao, Zhi-Hua Zhou. [doi]
• Simultaneous Preference and Metric Learning from Paired ComparisonsAustin Xu, Mark A. Davenport. [doi]
• A convex optimization formulation for multivariate regressionYunzhang Zhu. [doi]
• Inference Stage Optimization for Cross-scenario 3D Human Pose EstimationJianfeng Zhang, Xuecheng Nie, Jiashi Feng. [doi]
• wav2vec 2.0: A Framework for Self-Supervised Learning of Speech RepresentationsAlexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, Michael Auli. [doi]
• Fair regression via plug-in estimator and recalibration with statistical guaranteesEvgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil. [doi]
• BRP-NAS: Prediction-based NAS using GCNsLukasz Dudziak, Thomas C. P. Chau, Mohamed S. Abdelfattah, Royson Lee, Hyeji Kim, Nicholas D. Lane. [doi]
• Neural encoding with visual attentionMeenakshi Khosla, Gia H. Ngo, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu. [doi]
• Projected Stein Variational Gradient DescentPeng Chen 0024, Omar Ghattas. [doi]
• Partial Optimal Tranport with applications on Positive-Unlabeled LearningLaetitia Chapel, Mokhtar Z. Alaya, Gilles Gasso. [doi]
• Task-Robust Model-Agnostic Meta-LearningLiam Collins, Aryan Mokhtari, Sanjay Shakkottai. [doi]
• A shooting formulation of deep learningFrançois-Xavier Vialard, Roland Kwitt, Susan Wei, Marc Niethammer. [doi]
• Minimax Optimal Nonparametric Estimation of Heterogeneous Treatment EffectsZijun Gao, Yanjun Han. [doi]
• Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit ConstraintsMarc Finzi, Ke Alexander Wang, Andrew Gordon Wilson. [doi]
• Understanding the Role of Training Regimes in Continual LearningSeyed-Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan Ghasemzadeh. [doi]
• Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement LearningCong Zhang, Wen Song, Zhiguang Cao, Jie Zhang 0002, Puay Siew Tan, Chi Xu. [doi]
• A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability DistributionsYulong Lu, Jianfeng Lu 0001. [doi]
• SurVAE Flows: Surjections to Bridge the Gap between VAEs and FlowsDidrik Nielsen, Priyank Jaini, Emiel Hoogeboom, Ole Winther, Max Welling. [doi]
• Sparse and Continuous Attention MechanismsAndré F. T. Martins, António Farinhas, Marcos V. Treviso, Vlad Niculae, Pedro M. Q. Aguiar, Mário A. T. Figueiredo. [doi]
• Implicit Bias in Deep Linear Classification: Initialization Scale vs Training AccuracyEdward Moroshko, Blake E. Woodworth, Suriya Gunasekar, Jason D. Lee, Nati Srebro, Daniel Soudry. [doi]
• Provable Online CP/PARAFAC Decomposition of a Structured Tensor via Dictionary LearningSirisha Rambhatla, Xingguo Li, Jarvis D. Haupt. [doi]
• Certifiably Adversarially Robust Detection of Out-of-Distribution DataJulian Bitterwolf, Alexander Meinke, Matthias Hein 0001. [doi]
• DisARM: An Antithetic Gradient Estimator for Binary Latent VariablesZhe Dong, Andriy Mnih, George Tucker. [doi]
• AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep LearningHao Zhang 0025, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing. [doi]
• Exactly Computing the Local Lipschitz Constant of ReLU NetworksMatt Jordan, Alexandros G. Dimakis. [doi]
• The Flajolet-Martin Sketch Itself Preserves Differential Privacy: Private Counting with Minimal SpaceAdam D. Smith, Shuang Song 0001, Abhradeep Thakurta. [doi]
• Understanding Gradient Clipping in Private SGD: A Geometric PerspectiveXiangyi Chen, Steven Z. Wu, Mingyi Hong. [doi]
• Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and RobustnessLong Zhao 0003, Ting Liu 0005, Xi Peng 0005, Dimitris N. Metaxas. [doi]
• Novelty Search in Representational Space for Sample Efficient ExplorationRuo Yu Tao, Vincent François-Lavet, Joelle Pineau. [doi]
• The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic ModelsYingxiang Yang, Negar Kiyavash, Le Song, Niao He. [doi]
• What if Neural Networks had SVDs?Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery, Davide Mottin. [doi]
• Learning Loss for Test-Time AugmentationIldoo Kim, Younghoon Kim, Sungwoong Kim. [doi]
• A graph similarity for deep learningSeongmin Ok. [doi]
• Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization BoundsHassan Hafez-Kolahi, Zeinab Golgooni, Shohreh Kasaei, Mahdieh Soleymani. [doi]
• Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted RetrainingAustin Tripp, Erik A. Daxberger, José Miguel Hernández-Lobato. [doi]
• Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is EnoughMao Ye, Lemeng Wu, Qiang Liu 0001. [doi]
• A General Large Neighborhood Search Framework for Solving Integer Linear ProgramsJialin Song, Ravi Lanka, Yisong Yue, Bistra Dilkina. [doi]
• Estimating the Effects of Continuous-valued Interventions using Generative Adversarial NetworksIoana Bica, James Jordon, Mihaela van der Schaar. [doi]
• Least Squares Regression with Markovian Data: Fundamental Limits and AlgorithmsDheeraj Nagaraj, Xian Wu, Guy Bresler, Prateek Jain 0002, Praneeth Netrapalli. [doi]
• Counterfactual Data Augmentation using Locally Factored DynamicsSilviu Pitis, Elliot Creager, Animesh Garg. [doi]
• Distributionally Robust Federated AveragingYuyang Deng, Mohammad Mahdi Kamani, Mehrdad Mahdavi. [doi]
• Sequence to Multi-Sequence Learning via Conditional Chain Mapping for Mixture SignalsJing Shi 0003, Xuankai Chang, Pengcheng Guo, Shinji Watanabe 0001, Yusuke Fujita, Jiaming Xu 0001, Bo Xu 0002, Lei Xie. [doi]
• Convergence and Stability of Graph Convolutional Networks on Large Random GraphsNicolas Keriven, Alberto Bietti, Samuel Vaiter. [doi]
• Information-theoretic Task Selection for Meta-Reinforcement LearningRicardo Luna Gutierrez, Matteo Leonetti. [doi]
• Learning with Differentiable Pertubed OptimizersQuentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach. [doi]
• Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic SegmentationYangxin Wu, Gengwei Zhang, Hang Xu, Xiaodan Liang, Liang Lin. [doi]
• Deep Diffusion-Invariant Wasserstein Distributional ClassificationSung-Woo Park, Dong Wook Shu, Junseok Kwon. [doi]
• Batch normalization provably avoids ranks collapse for randomly initialised deep networksHadi Daneshmand, Jonas Moritz Kohler, Francis R. Bach, Thomas Hofmann, Aurélien Lucchi. [doi]
• PyGlove: Symbolic Programming for Automated Machine LearningDaiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Gabriel Bender, Hanxiao Liu, Adam Kraft, Chen Liang, Quoc Le 0001. [doi]
• Implicit Graph Neural NetworksFangda Gu, Heng Chang, Wenwu Zhu 0001, Somayeh Sojoudi, Laurent El Ghaoui. [doi]
• Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous GraphsDasol Hwang, Jinyoung Park, Sunyoung Kwon, Kyung Min Kim, Jung-Woo Ha 0001, Hyunwoo J. Kim. [doi]
• Continual Learning of a Mixed Sequence of Similar and Dissimilar TasksZixuan Ke, Bing Liu, Xingchang Huang. [doi]
• On the Error Resistance of Hinge-Loss MinimizationKunal Talwar. [doi]
• Consistent feature selection for analytic deep neural networksVu C. Dinh, Lam Si Tung Ho. [doi]
• Minibatch vs Local SGD for Heterogeneous Distributed LearningBlake E. Woodworth, Kumar Kshitij Patel, Nati Srebro. [doi]
• Geometric Dataset Distances via Optimal TransportDavid Alvarez-Melis, Nicolò Fusi. [doi]
• Manifold structure in graph embeddingsPatrick Rubin-Delanchy. [doi]
• A Biologically Plausible Neural Network for Slow Feature AnalysisDavid Lipshutz, Charles Windolf, Siavash Golkar, Dmitri B. Chklovskii. [doi]
• The Wasserstein Proximal Gradient AlgorithmAdil Salim, Anna Korba, Giulia Luise. [doi]
• Listening to Sounds of Silence for Speech DenoisingRuilin Xu 0001, Rundi Wu, Yuko Ishiwaka, Carl Vondrick, Changxi Zheng. [doi]
• Differentiable Top-k with Optimal TransportYujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei 0025, Tomas Pfister. [doi]
• Submodular Meta-LearningArman Adibi, Aryan Mokhtari, Hamed Hassani. [doi]
• Exact expressions for double descent and implicit regularization via surrogate random designMichal Derezinski, Feynman T. Liang, Michael W. Mahoney. [doi]
• Demystifying Orthogonal Monte Carlo and BeyondHan Lin, Haoxian Chen, Krzysztof Marcin Choromanski, Tianyi Zhang, Clement Laroche. [doi]
• What is being transferred in transfer learning?Behnam Neyshabur, Hanie Sedghi, Chiyuan Zhang. [doi]
• Truncated Linear Regression in High DimensionsConstantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis. [doi]
• The phase diagram of approximation rates for deep neural networksDmitry Yarotsky, Anton Zhevnerchuk. [doi]
• Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian OptimizationSreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh. [doi]
• Confidence sequences for sampling without replacementIan Waudby-Smith, Aaditya Ramdas. [doi]
• Unsupervised Representation Learning by Invariance PropagationFeng Wang 0034, Huaping Liu 0001, Di Guo, Fuchun Sun. [doi]
• Disentangling Human Error from Ground Truth in Segmentation of Medical ImagesLe Zhang, Ryutaro Tanno, Moucheng Xu, Chen Jin, Joseph Jacob, Olga Cicarrelli, Frederik Barkhof, Daniel C. Alexander. [doi]
• Domain Generalization for Medical Imaging Classification with Linear-Dependency RegularizationHaoliang Li, Yufei Wang, Renjie Wan, Shiqi Wang 0001, Tie-Qiang Li, Alex C. Kot. [doi]
• Efficient active learning of sparse halfspaces with arbitrary bounded noiseChicheng Zhang, Jie Shen 0005, Pranjal Awasthi. [doi]
• A simple normative network approximates local non-Hebbian learning in the cortexSiavash Golkar, David Lipshutz, Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii. [doi]
• Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient DescentDimitris Fotakis, Thanasis Lianeas, Georgios Piliouras, Stratis Skoulakis. [doi]
• Efficient Projection-free Algorithms for Saddle Point ProblemsCheng Chen, Luo Luo, Weinan Zhang 0001, Yong Yu 0001. [doi]
• An Unsupervised Information-Theoretic Perceptual Quality MetricSangnie Bhardwaj, Ian Fischer, Johannes Ballé, Troy T. Chinen. [doi]
• Black-Box Optimization with Local Generative SurrogatesSergey Shirobokov, Vladislav Belavin, Michael Kagan, Andrey Ustyuzhanin, Atilim Gunes Baydin. [doi]
• Combining Deep Reinforcement Learning and Search for Imperfect-Information GamesNoam Brown, Anton Bakhtin, Adam Lerer, Qucheng Gong. [doi]
• Inverting Gradients - How easy is it to break privacy in federated learning?Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller 0001. [doi]
• Dense Correspondences between Human Bodies via Learning Transformation Synchronization on GraphsXiangru Huang, Haitao Yang, Etienne Vouga, Qixing Huang. [doi]
• Variational Interaction Information Maximization for Cross-domain DisentanglementHyeongJoo Hwang, Geon-hyeong Kim, Seunghoon Hong, Kee-Eung Kim. [doi]
• Big Self-Supervised Models are Strong Semi-Supervised LearnersTing Chen, Simon Kornblith, Kevin Swersky, Mohammad Norouzi 0002, Geoffrey E. Hinton. [doi]
• The Potts-Ising model for discrete multivariate dataZahra S. Razaee, Arash A. Amini. [doi]
• Constrained episodic reinforcement learning in concave-convex and knapsack settingsKianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun. [doi]
• Deep Smoothing of the Implied Volatility SurfaceDamien Ackerer, Natasa Tagasovska, Thibault Vatter. [doi]
• Language and Visual Entity Relationship Graph for Agent NavigationYicong Hong, Cristian Rodriguez Opazo, Yuankai Qi, Qi Wu 0001, Stephen Gould. [doi]
• Sequential Bayesian Experimental Design with Variable Cost StructureSue Zheng, David S. Hayden, Jason Pacheco, John W. Fisher III. [doi]
• Locally private non-asymptotic testing of discrete distributions is faster using interactive mechanismsThomas Berrett, Cristina Butucea. [doi]
• Bandit Linear ControlAsaf Cassel, Tomer Koren. [doi]
• Interpretable multi-timescale models for predicting fMRI responses to continuous natural speechShailee Jain, Vy A. Vo, Shivangi Mahto, Amanda LeBel, Javier S. Turek, Alexander Huth. [doi]
• Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the WebZhenwei Dai, Anshumali Shrivastava. [doi]
• The Power of Comparisons for Actively Learning Linear ClassifiersMax Hopkins, Daniel Kane, Shachar Lovett. [doi]
• JAX MD: A Framework for Differentiable PhysicsSamuel S. Schoenholz, Ekin Dogus Cubuk. [doi]
• Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link PredictionJinheon Baek, Dong-Bok Lee, Sung Ju Hwang. [doi]
• Audeo: Audio Generation for a Silent Performance VideoKun Su, Xiulong Liu, Eli Shlizerman. [doi]
• Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed RewardsKyungjae Lee, Hongjun Yang, Sungbin Lim, Songhwai Oh. [doi]
• CSER: Communication-efficient SGD with Error ResetCong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin. [doi]
• Bandit Samplers for Training Graph Neural NetworksZiqi Liu, Zhengwei Wu, Zhiqiang Zhang 0012, Jun Zhou 0011, Shuang Yang, Le Song, Yuan Qi 0001. [doi]
• Neural Networks with Small Weights and Depth-Separation BarriersGal Vardi, Ohad Shamir. [doi]
• Fast and Accurate $k$-means++ via Rejection SamplingVincent Cohen-Addad, Silvio Lattanzi, Ashkan Norouzi-Fard, Christian Sohler, Ola Svensson. [doi]
• Multimodal Generative Learning Utilizing Jensen-Shannon-DivergenceThomas M. Sutter, Imant Daunhawer, Julia E. Vogt. [doi]
• Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding WalksJingqiu Ding, Samuel B. Hopkins, David Steurer. [doi]
• Strongly Incremental Constituency Parsing with Graph Neural NetworksKaiyu Yang, Jia Deng. [doi]
• Delving into the Cyclic Mechanism in Semi-supervised Video Object SegmentationYuxi Li, Ning Xu 0007, Jinlong Peng, John See, Weiyao Lin. [doi]
• Storage Efficient and Dynamic Flexible Runtime Channel Pruning via Deep Reinforcement LearningJianda Chen, Shangyu Chen, Sinno Jialin Pan. [doi]
• Penalized Langevin dynamics with vanishing penalty for smooth and log-concave targetsAvetik G. Karagulyan, Arnak S. Dalalyan. [doi]
• Black-Box Certification with Randomized Smoothing: A Functional Optimization Based FrameworkDinghuai Zhang, Mao Ye, ChengYue Gong, Zhanxing Zhu, Qiang Liu 0001. [doi]
• Tight First- and Second-Order Regret Bounds for Adversarial Linear BanditsShinji Ito, Shuichi Hirahara, Tasuku Soma, Yuichi Yoshida. [doi]
• Accelerating Reinforcement Learning through GPU Atari EmulationSteven Dalton, Iuri Frosio. [doi]
• The Generalized Lasso with Nonlinear Observations and Generative PriorsZhaoqiang Liu, Jonathan Scarlett. [doi]
• VAEM: a Deep Generative Model for Heterogeneous Mixed Type DataChao Ma, Sebastian Tschiatschek, Richard E. Turner, José Miguel Hernández-Lobato, Cheng Zhang. [doi]
• Spike and slab variational Bayes for high dimensional logistic regressionKolyan Ray, Botond Szabó, Gabriel Clara. [doi]
• Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised LearningJaehyung Kim, Youngbum Hur, Sejun Park, Eunho Yang, Sung Ju Hwang, Jinwoo Shin. [doi]
• Towards a Better Global Loss Landscape of GANsRuoyu Sun 0001, Tiantian Fang, Alexander G. Schwing. [doi]
• Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-IDYixiao Ge, Feng Zhu 0006, Dapeng Chen, Rui Zhao 0001, Hongsheng Li. [doi]
• Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent KernelStanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul, Sepideh Kharaghani, Daniel M. Roy 0001, Surya Ganguli. [doi]
• On the distance between two neural networks and the stability of learningJeremy Bernstein, Arash Vahdat, Yisong Yue, Ming-Yu Liu 0001. [doi]
• Learning the Geometry of Wave-Based ImagingKonik Kothari, Maarten V. De Hoop, Ivan Dokmanic. [doi]
• Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and PlanningSebastian Curi, Felix Berkenkamp, Andreas Krause 0001. [doi]
• Fourier Sparse Leverage Scores and Approximate Kernel LearningTamás Erdélyi, Cameron Musco, Christopher Musco. [doi]
• Dynamic Fusion of Eye Movement Data and Verbal Narrations in Knowledge-rich DomainsErvine Zheng, Qi Yu 0001, Rui Li 0002, Pengcheng Shi, Anne R. Haake. [doi]
• MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained TransformersWenhui Wang, Furu Wei, Li Dong 0004, Hangbo Bao, Nan Yang 0002, Ming Zhou 0001. [doi]
• Decentralized TD Tracking with Linear Function Approximation and its Finite-Time AnalysisGang Wang 0014, Songtao Lu, Georgios B. Giannakis, Gerald Tesauro, Jian Sun 0003. [doi]
• Information Theoretic Regret Bounds for Online Nonlinear ControlSham M. Kakade, Akshay Krishnamurthy, Kendall Lowrey, Motoya Ohnishi, Wen Sun. [doi]
• Learning Retrospective Knowledge with Reverse Reinforcement LearningShangtong Zhang, Vivek Veeriah, Shimon Whiteson. [doi]
• Decisions, Counterfactual Explanations and Strategic BehaviorStratis Tsirtsis, Manuel Gomez-Rodriguez. [doi]
• Deep Variational Instance SegmentationJialin Yuan, Chao Chen, Fuxin Li. [doi]
• Fine-Grained Dynamic Head for Object DetectionLin Song, Yanwei Li, Zhengkai Jiang, Zeming Li, Hongbin Sun 0001, Jian Sun 0015, Nanning Zheng 0001. [doi]
• Probabilistic Fair ClusteringSeyed A. Esmaeili, Brian Brubach, Leonidas Tsepenekas, John Dickerson 0001. [doi]
• Off-Policy Imitation Learning from ObservationsZhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou. [doi]
• VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular DomainJinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar. [doi]
• Training Generative Adversarial Networks by Solving Ordinary Differential EquationsChongli Qin, Yan Wu, Jost Tobias Springenberg, Andy Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli. [doi]
• Improving model calibration with accuracy versus uncertainty optimizationRanganath Krishnan, Omesh Tickoo. [doi]
• Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based AlgorithmsXiangyi Chen, Tiancong Chen, Haoran Sun, Steven Z. Wu, Mingyi Hong. [doi]
• Introducing Routing Uncertainty in Capsule NetworksFabio De Sousa Ribeiro, Georgios Leontidis, Stefanos D. Kollias. [doi]
• Reverse-engineering recurrent neural network solutions to a hierarchical inference task for miceRylan Schaeffer, Mikail Khona, Leenoy Meshulam, International Brain Laboratory, Ila Fiete. [doi]
• A Unified View of Label Shift EstimationSaurabh Garg, Yifan Wu, Sivaraman Balakrishnan, Zachary C. Lipton. [doi]
• Is Plug-in Solver Sample-Efficient for Feature-based Reinforcement Learning?Qiwen Cui, Lin F. Yang. [doi]
• Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted DataQian Lou, Bo Feng, Geoffrey Charles Fox, Lei Jiang 0001. [doi]
• DISK: Learning local features with policy gradientMichal J. Tyszkiewicz, Pascal Fua, Eduard Trulls. [doi]
• On Convergence and Generalization of Dropout TrainingPoorya Mianjy, Raman Arora. [doi]
• Object-Centric Learning with Slot AttentionFrancesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, Thomas Kipf. [doi]
• Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative PriorsJorio Cocola, Paul Hand, Vladislav Voroninski. [doi]
• Neural Architecture Generator OptimizationRobin Ru, Pedro M. Esperança, Fabio Maria Carlucci. [doi]
• Comprehensive Attention Self-Distillation for Weakly-Supervised Object DetectionZeyi Huang, Yang Zou, B. V. K. Vijaya Kumar, Dong Huang. [doi]
• Hypersolvers: Toward Fast Continuous-Depth ModelsMichael Poli, Stefano Massaroli, Atsushi Yamashita, Hajime Asama, Jinkyoo Park. [doi]
• The interplay between randomness and structure during learning in RNNsFriedrich Schüßler, Francesca Mastrogiuseppe, Alexis M. Dubreuil, Srdjan Ostojic, Omri Barak. [doi]
• Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyondCharles C. Margossian, Aki Vehtari, Daniel Simpson, Raj Agrawal. [doi]
• Guiding Deep Molecular Optimization with Genetic ExplorationSungsoo Ahn, Junsu Kim, Hankook Lee, Jinwoo Shin. [doi]
• Node Embeddings and Exact Low-Rank Representations of Complex NetworksSudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis. [doi]
• Neuron Shapley: Discovering the Responsible NeuronsAmirata Ghorbani, James Y. Zou. [doi]
• Neural Manifold Ordinary Differential EquationsAaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa. [doi]
• Disentangling by Subspace DiffusionDavid Pfau, Irina Higgins, Aleksandar Botev, Sébastien Racanière. [doi]
• Probabilistic Circuits for Variational Inference in Discrete Graphical ModelsAndy Shih, Stefano Ermon. [doi]
• Sparse Symplectically Integrated Neural NetworksDaniel M. DiPietro, Shiying Xiong, Bo Zhu. [doi]
• Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response JacobiansJuhan Bae, Roger B. Grosse. [doi]
• Collapsing Bandits and Their Application to Public Health InterventionAditya Mate, Jackson A. Killian, Haifeng Xu, Andrew Perrault, Milind Tambe. [doi]
• Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step TreesShali Jiang 0001, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett. [doi]
• Deep Direct Likelihood KnockoffsMukund Sudarshan, Wesley Tansey, Rajesh Ranganath. [doi]
• A Theoretical Framework for Target PropagationAlexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens, João Sacramento, Benjamin F. Grewe. [doi]
• Better Set Representations For Relational ReasoningQian Huang, Horace He, Abhay Singh, Yan Zhang, Ser-Nam Lim, Austin R. Benson. [doi]
• Accelerating Training of Transformer-Based Language Models with Progressive Layer DroppingMinjia Zhang, Yuxiong He. [doi]
• Continual Learning with Node-Importance based Adaptive Group Sparse RegularizationSangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon. [doi]
• ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution MappingCher Bass, Mariana da Silva, Carole H. Sudre, Petru-Daniel Tudosiu, Stephen M. Smith, Emma C. Robinson. [doi]
• Implicit Regularization and Convergence for Weight NormalizationXiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu. [doi]
• Adaptive Online Estimation of Piecewise Polynomial TrendsDheeraj Baby, Yu-Xiang Wang. [doi]
• DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid PoolingMoshe Eliasof, Eran Treister. [doi]
• Provably Efficient Reward-Agnostic Navigation with Linear Value IterationAndrea Zanette, Alessandro Lazaric, Mykel J. Kochenderfer, Emma Brunskill. [doi]
• Zap Q-Learning With Nonlinear Function ApproximationShuhang Chen, Adithya M. Devraj, Fan Lu, Ana Busic, Sean P. Meyn. [doi]
• Agnostic Learning of a Single Neuron with Gradient DescentSpencer Frei, Yuan Cao, Quanquan Gu. [doi]
• Fast Fourier ConvolutionLu Chi, Borui Jiang, Yadong Mu. [doi]
• Real World Games Look Like Spinning TopsWojciech M. Czarnecki, Gauthier Gidel, Brendan Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg. [doi]
• An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear BanditsAndrea Tirinzoni, Matteo Pirotta, Marcello Restelli, Alessandro Lazaric. [doi]
• Inferring learning rules from animal decision-makingZoe Ashwood, Nicholas A. Roy, Ji Hyun Bak, Jonathan W. Pillow. [doi]
• Interpretable Sequence Learning for Covid-19 ForecastingSercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh 0005, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister. [doi]
• An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient MethodsYanli Liu 0003, Kaiqing Zhang, Tamer Basar, Wotao Yin. [doi]
• Inverse Learning of SymmetriesMario Wieser, Sonali Parbhoo, Aleksander Wieczorek, Volker Roth 0001. [doi]
• Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learningChandrashekar Lakshminarayanan, Amit Vikram Singh. [doi]
• Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder DimensionRuosong Wang, Russ R. Salakhutdinov, Lin F. Yang. [doi]
• Algorithmic recourse under imperfect causal knowledge: a probabilistic approachAmir-Hossein Karimi, Bodo Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera. [doi]
• Enabling certification of verification-agnostic networks via memory-efficient semidefinite programmingSumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli. [doi]
• A Bayesian Nonparametrics View into Deep RepresentationsMichal Jamróz, Marcin Kurdziel, Mateusz Opala. [doi]
• A Computational Separation between Private Learning and Online LearningMark Bun. [doi]
• Online Agnostic Boosting via Regret MinimizationNataly Brukhim, Xinyi Chen, Elad Hazan, Shay Moran. [doi]
• Evaluating and Rewarding Teamwork Using Cooperative Game AbstractionsTom Yan, Christian Kroer, Alexander Peysakhovich. [doi]
• Generalized Leverage Score Sampling for Neural NetworksJason D. Lee, Ruoqi Shen, Zhao Song 0002, Mengdi Wang, Zheng Yu. [doi]
• Smoothed Analysis of Online and Differentially Private LearningNika Haghtalab, Tim Roughgarden, Abhishek Shetty. [doi]
• AdaTune: Adaptive Tensor Program Compilation Made EfficientMenghao Li, Minjia Zhang, Chi Wang, Mingqin Li. [doi]
• Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase RetrievalStefano Sarao Mannelli, Giulio Biroli, Chiara Cammarota, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová. [doi]
• Group-Fair Online Allocation in Continuous TimeSemih Cayci, Swati Gupta, Atilla Eryilmaz. [doi]
• An operator view of policy gradient methodsDibya Ghosh, Marlos C. Machado, Nicolas Le Roux. [doi]
• Bayesian Multi-type Mean Field Multi-agent Imitation LearningFan Yang, Alina Vereshchaka, Changyou Chen, Wen Dong 0001. [doi]
• Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and FeaturesRobin Schirrmeister, Yuxuan Zhou, Tonio Ball, Dan Zhang. [doi]
• Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNetsKai Han, Yunhe Wang, Qiulin Zhang, Wei Zhang, Chunjing Xu, Tong Zhang. [doi]
• Learning Compositional Rules via Neural Program SynthesisMaxwell I. Nye, Armando Solar-Lezama, Josh Tenenbaum 0001, Brenden M. Lake. [doi]
• Off-Policy Interval Estimation with Lipschitz Value IterationZiyang Tang, Yihao Feng, Na Zhang, Jian Peng 0001, Qiang Liu 0001. [doi]
• Generating Correct Answers for Progressive Matrices Intelligence TestsNiv Pekar, Yaniv Benny, Lior Wolf. [doi]
• Deep Metric Learning with Spherical EmbeddingDingyi Zhang, Yingming Li, Zhongfei Zhang. [doi]
• The Statistical Complexity of Early-Stopped Mirror DescentTomas Vaskevicius, Varun Kanade, Patrick Rebeschini. [doi]
• Neural Sparse Voxel FieldsLingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, Christian Theobalt. [doi]
• Information theoretic limits of learning a sparse ruleClément Luneau, Jean Barbier, Nicolas Macris. [doi]
• A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained OptimizationDigvijay Boob, Qi Deng, Guanghui Lan, Yilin Wang. [doi]
• Network Diffusions via Neural Mean-Field DynamicsShushan He, Hongyuan Zha, Xiaojing Ye. [doi]
• Equivariant Networks for Hierarchical StructuresRenhao Wang, Marjan Albooyeh, Siamak Ravanbakhsh. [doi]
• An Equivalence between Loss Functions and Non-Uniform Sampling in Experience ReplayScott Fujimoto, David Meger, Doina Precup. [doi]
• Generalized Independent Noise Condition for Estimating Latent Variable Causal GraphsFeng Xie 0002, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang 0001. [doi]
• Deep Rao-Blackwellised Particle Filters for Time Series ForecastingRichard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus. [doi]
• Optimistic Dual Extrapolation for Coherent Non-monotone Variational InequalitiesChaobing Song, Zhengyuan Zhou, Yichao Zhou, Yong Jiang, Yi Ma 0001. [doi]
• Domain Adaptation with Conditional Distribution Matching and Generalized Label ShiftRemi Tachet des Combes, Han Zhao 0002, Yu-Xiang Wang, Geoffrey J. Gordon. [doi]
• On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling MethodYe He, Krishnakumar Balasubramanian, Murat A. Erdogdu. [doi]
• A Group-Theoretic Framework for Data AugmentationShuxiao Chen, Edgar Dobriban, Jane H. Lee. [doi]
• A Matrix Chernoff Bound for Markov Chains and Its Application to Co-occurrence MatricesJiezhong Qiu, Chi Wang 0001, Ben Liao, Richard Peng, Jie Tang 0001. [doi]
• Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known TransitionTiancheng Jin, Haipeng Luo. [doi]
• Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset BiasesSenthil Purushwalkam, Abhinav Gupta 0001. [doi]
• Continuous Submodular Maximization: Beyond DR-SubmodularityMoran Feldman, Amin Karbasi. [doi]
• Bayesian filtering unifies adaptive and non-adaptive neural network optimization methodsLaurence Aitchison. [doi]
• Decision-Making with Auto-Encoding Variational BayesRomain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier. [doi]
• Learning Physical Constraints with Neural ProjectionsShuqi Yang, Xingzhe He, Bo Zhu. [doi]
• Regret Bounds without Lipschitz Continuity: Online Learning with Relative-Lipschitz LossesYihan Zhou, Victor S. Portella, Mark Schmidt 0001, Nicholas J. A. Harvey. [doi]
• Sparse Graphical Memory for Robust PlanningScott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak. [doi]
• Linear Disentangled Representations and Unsupervised Action EstimationMatthew Painter, Adam Prügel-Bennett, Jonathon S. Hare. [doi]
• Variance reduction for Random Coordinate Descent-Langevin Monte CarloZhiyan Ding, Qin Li. [doi]
• Falcon: Fast Spectral Inference on Encrypted DataQian Lou, Wen-Jie Lu, Cheng Hong, Lei Jiang 0001. [doi]
• Learning Deformable Tetrahedral Meshes for 3D ReconstructionJun Gao, Wenzheng Chen, Tommy Xiang, Alec Jacobson, Morgan McGuire, Sanja Fidler. [doi]
• Fair Performance Metric ElicitationGaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo. [doi]
• Near-Optimal Comparison Based ClusteringMichaël Perrot, Pascal Mattia Esser, Debarghya Ghoshdastidar. [doi]
• Avoiding Side Effects in Complex EnvironmentsAlexander Matt Turner, Neale Ratzlaff, Prasad Tadepalli. [doi]
• One Ring to Rule Them All: Certifiably Robust Geometric Perception with OutliersHeng Yang 0002, Luca Carlone. [doi]
• Universal Function Approximation on GraphsRickard Brüel Gabrielsson. [doi]
• Scalable Graph Neural Networks via Bidirectional PropagationMing Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan 0001, Xiaoyong Du 0001, Ji-Rong Wen. [doi]
• Learning Dynamic Belief Graphs to Generalize on Text-Based GamesAshutosh Adhikari, Xingdi Yuan, Marc-Alexandre Côté, Mikulas Zelinka, Marc-Antoine Rondeau, Romain Laroche, Pascal Poupart, Jian Tang, Adam Trischler, William L. Hamilton. [doi]
• NVAE: A Deep Hierarchical Variational AutoencoderArash Vahdat, Jan Kautz. [doi]
• Multi-task Causal Learning with Gaussian ProcessesVirginia Aglietti, Theodoros Damoulas, Mauricio Álvarez, Javier Gonzalez. [doi]
• Reservoir Computing meets Recurrent Kernels and Structured TransformsJonathan Dong, Ruben Ohana, Mushegh Rafayelyan, Florent Krzakala. [doi]
• Passport-aware Normalization for Deep Model ProtectionJie Zhang, Dongdong Chen 0001, Jing Liao 0001, Weiming Zhang, Gang Hua 0001, Nenghai Yu. [doi]
• Coresets for Robust Training of Deep Neural Networks against Noisy LabelsBaharan Mirzasoleiman, Kaidi Cao, Jure Leskovec. [doi]
• Neural Star Domain as Primitive RepresentationYuki Kawana, Yusuke Mukuta, Tatsuya Harada. [doi]
• On Numerosity of Deep Neural NetworksXi Zhang, Xiaolin Wu. [doi]
• AttendLight: Universal Attention-Based Reinforcement Learning Model for Traffic Signal ControlAfshin Oroojlooy, MohammadReza Nazari, Davood Hajinezhad, Jorge Silva. [doi]
• Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory NeuronsQianyi Li, Cengiz Pehlevan. [doi]
• Robust Optimization for Fairness with Noisy Protected GroupsSerena Wang, Wenshuo Guo, Harikrishna Narasimhan, Andrew Cotter, Maya R. Gupta, Michael I. Jordan. [doi]
• High-Throughput Synchronous Deep RLIou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing. [doi]
• Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical ApproximationsZhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck. [doi]
• Attribute Prototype Network for Zero-Shot LearningWenjia Xu, Yongqin Xian, Jiuniu Wang, Bernt Schiele, Zeynep Akata. [doi]
• Learning About Objects by Learning to Interact with ThemMartin Lohmann, Jordi Salvador, Aniruddha Kembhavi, Roozbeh Mottaghi. [doi]
• RATT: Recurrent Attention to Transient Tasks for Continual Image CaptioningRiccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer 0001. [doi]
• Approximate Heavily-Constrained Learning with Lagrange Multiplier ModelsHarikrishna Narasimhan, Andrew Cotter, Yichen Zhou, Serena Wang, Wenshuo Guo. [doi]
• Federated Principal Component AnalysisAndreas Grammenos, Rodrigo Mendoza-Smith, Jon Crowcroft, Cecilia Mascolo. [doi]
• High-recall causal discovery for autocorrelated time series with latent confoundersAndreas Gerhardus, Jakob Runge. [doi]
• Random Walk Graph Neural NetworksGiannis Nikolentzos, Michalis Vazirgiannis. [doi]
• Metric-Free Individual Fairness in Online LearningYahav Bechavod, Christopher Jung, Steven Z. Wu. [doi]
• Weston-Watkins Hinge Loss and Ordered PartitionsYutong Wang, Clayton Scott. [doi]
• Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret MinimizationSamuel B. Hopkins, Jerry Li 0001, Fred Zhang. [doi]
• Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task LassoJérôme-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort, Bertrand Thirion. [doi]
• Reward Propagation Using Graph Convolutional NetworksMartin Klissarov, Doina Precup. [doi]
• Regression with reject option and application to kNNAhmed Zaoui, Christophe Denis, Mohamed Hebiri. [doi]
• Minimax Estimation of Conditional Moment ModelsNishanth Dikkala, Greg Lewis, Lester Mackey, Vasilis Syrgkanis. [doi]
• Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack ConstraintGeorgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Rebecca Reiffenhäuser. [doi]
• Long-Horizon Visual Planning with Goal-Conditioned Hierarchical PredictorsKarl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine. [doi]
• Mutual exclusivity as a challenge for deep neural networksKanishk Gandhi, Brenden M. Lake. [doi]
• Scattering GCN: Overcoming Oversmoothness in Graph Convolutional NetworksYimeng Min, Frederik Wenkel, Guy Wolf. [doi]
• Neural Execution Engines: Learning to Execute SubroutinesYujun Yan, Kevin Swersky, Danai Koutra, Parthasarathy Ranganathan, Milad Hashemi. [doi]
• On Testing of SamplersKuldeep S. Meel, Yash Pote, Sourav Chakraborty 0001. [doi]
• A mathematical theory of cooperative communicationPei Wang, Junqi Wang, Pushpi Paranamana, Patrick Shafto. [doi]
• Characterizing emergent representations in a space of candidate learning rules for deep networksYinan Cao, Christopher Summerfield, Andrew Saxe. [doi]
• ShiftAddNet: A Hardware-Inspired Deep NetworkHaoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin. [doi]
• Labelling unlabelled videos from scratch with multi-modal self-supervisionYuki Markus Asano, Mandela Patrick, Christian Rupprecht 0001, Andrea Vedaldi. [doi]
• Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data AugmentationSajad Norouzi, David J. Fleet, Mohammad Norouzi 0002. [doi]
• POMO: Policy Optimization with Multiple Optima for Reinforcement LearningYeong-Dae Kwon, Jinho Choo, Byoungjip Kim, Iljoo Yoon, Youngjune Gwon, Seungjai Min. [doi]
• Restoring Negative Information in Few-Shot Object DetectionYukuan Yang, Fangyun Wei, Miaojing Shi, Guoqi Li. [doi]
• AOT: Appearance Optimal Transport Based Identity Swapping for Forgery DetectionHao Zhu, Chaoyou Fu, Qianyi Wu, Wayne Wu, Chen Qian 0006, Ran He. [doi]
• Riemannian Continuous Normalizing FlowsEmile Mathieu, Maximilian Nickel. [doi]
• RNNPool: Efficient Non-linear Pooling for RAM Constrained InferenceOindrila Saha, Aditya Kusupati, Harsha Vardhan Simhadri, Manik Varma, Prateek Jain 0002. [doi]
• Dual T: Reducing Estimation Error for Transition Matrix in Label-noise LearningYu Yao, Tongliang Liu, Bo Han 0003, Mingming Gong, Jiankang deng, Gang Niu 0001, Masashi Sugiyama. [doi]
• Personalized Federated Learning with Moreau EnvelopesCanh T. Dinh, Nguyen H. Tran, Tuan-Dung Nguyen. [doi]
• Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive UncertaintiesJakob Lindinger, David Reeb, Christoph Lippert, Barbara Rakitsch. [doi]
• Taming Discrete Integration via the Boon of DimensionalityJeffrey M. Dudek, Dror Fried, Kuldeep S. Meel. [doi]
• A Tight Lower Bound and Efficient Reduction for Swap RegretShinji Ito. [doi]
• Markovian Score Climbing: Variational Inference with KL(p||q)Christian A. Naesseth, Fredrik Lindsten, David M. Blei. [doi]
• AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularitySilviu-Marian Udrescu, Andrew Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark. [doi]
• Constraining Variational Inference with Geometric Jensen-Shannon DivergenceJacob Deasy, Nikola Simidjievski, Pietro Lió. [doi]
• BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled ImagesThu Nguyen-Phuoc, Christian Richardt, Long Mai, Yong-Liang Yang, Niloy J. Mitra. [doi]
• Rel3D: A Minimally Contrastive Benchmark for Grounding Spatial Relations in 3DAnkit Goyal, Kaiyu Yang, Dawei Yang, Jia Deng. [doi]
• How to Learn a Useful Critic? Model-based Action-Gradient-Estimator Policy OptimizationPierluca D'Oro, Wojciech Jaskowski. [doi]
• What shapes feature representations? Exploring datasets, architectures, and trainingKatherine L. Hermann, Andrew K. Lampinen. [doi]
• Non-Crossing Quantile Regression for Distributional Reinforcement LearningFan Zhou, Jianing Wang, Xingdong Feng. [doi]
• Classification Under Misspecification: Halfspaces, Generalized Linear Models, and EvolvabilitySitan Chen, Frederic Koehler, Ankur Moitra, Morris Yau. [doi]
• Understanding and Improving Fast Adversarial TrainingMaksym Andriushchenko, Nicolas Flammarion. [doi]
• When Counterpoint Meets Chinese Folk MelodiesNan Jiang, Sheng Jin 0007, Zhiyao Duan, Changshui Zhang. [doi]
• Online Bayesian Goal Inference for Boundedly Rational Planning AgentsTan Zhi-Xuan, Jordyn L. Mann, Tom Silver, Josh Tenenbaum 0001, Vikash Mansinghka. [doi]
• Counterfactual Predictions under Runtime ConfoundingAmanda Coston, Edward H. Kennedy, Alexandra Chouldechova. [doi]
• Efficient Variational Inference for Sparse Deep Learning with Theoretical GuaranteeJincheng Bai, Qifan Song, Guang Cheng. [doi]
• Near-Optimal Reinforcement Learning with Self-PlayYu Bai, Chi Jin, Tiancheng Yu. [doi]
• Fast and Flexible Temporal Point Processes with Triangular MapsOleksandr Shchur, Nicholas Gao, Marin Bilos, Stephan Günnemann. [doi]
• SAC: Accelerating and Structuring Self-Attention via Sparse Adaptive ConnectionXiaoya Li, Yuxian Meng, Mingxin Zhou, Qinghong Han, Fei Wu, Jiwei Li. [doi]
• Hold me tight! Influence of discriminative features on deep network boundariesGuillermo Ortiz-Jiménez, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard. [doi]
• Input-Aware Dynamic Backdoor AttackTuan-Anh Nguyen, Anh Tran. [doi]
• Quantile Propagation for Wasserstein-Approximate Gaussian ProcessesRui Zhang, Christian J. Walder, Edwin V. Bonilla, Marian-Andrei Rizoiu, Lexing Xie. [doi]
• Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomicsAlex Tseng, Avanti Shrikumar, Anshul Kundaje. [doi]
• Meta-trained agents implement Bayes-optimal agentsVladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega. [doi]
• Neural Message Passing for Multi-Relational Ordered and Recursive HypergraphsNaganand Yadati. [doi]
• Learning Certified Individually Fair RepresentationsAnian Ruoss, Mislav Balunovic, Marc Fischer, Martin T. Vechev. [doi]
• Neural Sparse Representation for Image RestorationYuchen Fan, Jiahui Yu, Yiqun Mei, Yulun Zhang, Yun Fu 0001, Ding Liu, Thomas S. Huang. [doi]
• Group Knowledge Transfer: Federated Learning of Large CNNs at the EdgeChaoyang He 0001, Murali Annavaram, Salman Avestimehr. [doi]
• An Optimal Elimination Algorithm for Learning a Best ArmAvinatan Hassidim, Ron Kupfer, Yaron Singer. [doi]
• Fast Unbalanced Optimal Transport on a TreeRyoma Sato, Makoto Yamada, Hisashi Kashima. [doi]
• Learning Robust Decision Policies from Observational DataMuhammad Osama, Dave Zachariah, Peter Stoica. [doi]
• Big Bird: Transformers for Longer SequencesManzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontañón, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed. [doi]
• Multi-Plane Program Induction with 3D Box PriorsYikai Li, Jiayuan Mao, Xiuming Zhang, Bill Freeman, Josh Tenenbaum 0001, Noah Snavely, Jiajun Wu 0001. [doi]
• MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and ArchitecturesJeongun Ryu, Jaewoong Shin, Haebeom Lee, Sung Ju Hwang. [doi]
• Few-shot Image Generation with Elastic Weight ConsolidationYijun Li, Richard Zhang 0001, Jingwan Lu, Eli Shechtman. [doi]
• Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networksRoman Pogodin, Peter E. Latham. [doi]
• Debiasing Averaged Stochastic Gradient Descent to handle missing valuesAude Sportisse, Claire Boyer, Aymeric Dieuleveut, Julie Josse. [doi]
• Exploiting Higher Order Smoothness in Derivative-free Optimization and Continuous BanditsArya Akhavan, Massimiliano Pontil, Alexandre B. Tsybakov. [doi]
• Fair Hierarchical ClusteringSara Ahmadian, Alessandro Epasto, Marina Knittel, Ravi Kumar 0001, Mohammad Mahdian, Benjamin Moseley, Philip Pham, Sergei Vassilvitskii, Yuyan Wang. [doi]
• Minimax Classification with 0-1 Loss and Performance GuaranteesSantiago Mazuelas, Andrea Zanoni, Aritz Pérez. [doi]
• Optimal Query Complexity of Secure Stochastic Convex OptimizationWei Tang, Chien-Ju Ho, Yang Liu 0018. [doi]
• Neural FFTs for Universal Texture Image SynthesisMorteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro. [doi]
• Restless-UCB, an Efficient and Low-complexity Algorithm for Online Restless BanditsSiwei Wang, Longbo Huang, John C. S. Lui. [doi]
• Choice BanditsArpit Agarwal, Nicholas Johnson, Shivani Agarwal 0001. [doi]
• Robust Correction of Sampling Bias using Cumulative Distribution FunctionsBijan Mazaheri, Siddharth Jain, Jehoshua Bruck. [doi]
• Unsupervised Translation of Programming LanguagesBaptiste Rozière, Marie-Anne Lachaux, Lowik Chanussot, Guillaume Lample. [doi]
• Trade-offs and Guarantees of Adversarial Representation Learning for Information ObfuscationHan Zhao 0002, Jianfeng Chi, Yuan Tian 0001, Geoffrey J. Gordon. [doi]
• Autoencoders that don't overfit towards the IdentityHarald Steck. [doi]
• Statistical Optimal Transport posed as Learning Kernel EmbeddingJagarlapudi Saketha Nath, Pratik Kumar Jawanpuria. [doi]
• Walking in the Shadow: A New Perspective on Descent Directions for Constrained MinimizationHassan Mortagy, Swati Gupta, Sebastian Pokutta. [doi]
• Probabilistic Time Series Forecasting with Shape and Temporal DiversityVincent Le Guen, Nicolas Thome. [doi]
• A Unifying View of Optimism in Episodic Reinforcement LearningGergely Neu, Ciara Pike-Burke. [doi]
• Bayesian Optimization of Risk MeasuresSait Cakmak, Raul Astudillo, Peter I. Frazier, Enlu Zhou. [doi]
• Learning Representations from Audio-Visual Spatial AlignmentPedro Morgado, Yi Li, Nuno Nvasconcelos. [doi]
• WoodFisher: Efficient Second-Order Approximation for Neural Network CompressionSidak Pal Singh, Dan Alistarh. [doi]
• Bayesian Deep Ensembles via the Neural Tangent KernelBobby He, Balaji Lakshminarayanan, Yee Whye Teh. [doi]
• Robust Pre-Training by Adversarial Contrastive LearningZiyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang. [doi]
• Co-exposure Maximization in Online Social NetworksSijing Tu, Çigdem Aslay, Aristides Gionis. [doi]
• A Continuous-Time Mirror Descent Approach to Sparse Phase RetrievalFan Wu, Patrick Rebeschini. [doi]
• Adversarial Training is a Form of Data-dependent Operator Norm RegularizationKevin Roth, Yannic Kilcher, Thomas Hofmann. [doi]
• Exploiting the Surrogate Gap in Online Multiclass ClassificationDirk van der Hoeven. [doi]
• Efficient Generation of Structured Objects with Constrained Adversarial NetworksLuca Di Liello, Pierfrancesco Ardino, Jacopo Gobbi, Paolo Morettin, Stefano Teso, Andrea Passerini. [doi]
• Learning Semantic-aware Normalization for Generative Adversarial NetworksHeliang Zheng, Jianlong Fu, Yanhong Zeng, Jiebo Luo, Zheng-Jun Zha. [doi]
• Multi-agent active perception with prediction rewardsMikko Lauri, Frans A. Oliehoek. [doi]
• Hierarchical Granularity Transfer LearningShaobo Min, Hongtao Xie, Hantao Yao, Xuran Deng, Zheng-Jun Zha, Yongdong Zhang 0001. [doi]
• Transferable Calibration with Lower Bias and Variance in Domain AdaptationXimei Wang, Mingsheng Long, Jianmin Wang 0001, Michael I. Jordan. [doi]
• 3D Multi-bodies: Fitting Sets of Plausible 3D Human Models to Ambiguous Image DataBenjamin Biggs, David Novotný, Sébastien Ehrhardt, Hanbyul Joo, Benjamin Graham, Andrea Vedaldi. [doi]
• Provably Efficient Neural GTD for Off-Policy LearningHoi-To Wai, Zhuoran Yang, Zhaoran Wang, Mingyi Hong. [doi]
• Unsupervised Data Augmentation for Consistency TrainingQizhe Xie, Zihang Dai, Eduard H. Hovy, Thang Luong, Quoc Le 0001. [doi]
• Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional DomainsMatthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, Ren Ng. [doi]
• Distributionally Robust Local Non-parametric Conditional EstimationViet Anh Nguyen, Fan Zhang, José H. Blanchet, Erick Delage, Yinyu Ye. [doi]
• An Unbiased Risk Estimator for Learning with Augmented ClassesYu-Jie Zhang, Peng Zhao 0006, Lanjihong Ma, Zhi-Hua Zhou. [doi]
• Convergence of Meta-Learning with Task-Specific Adaptation over Partial ParametersKaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor. [doi]
• On Learning Ising Models under Huber's Contamination ModelAdarsh Prasad, Vishwak Srinivasan, Sivaraman Balakrishnan, Pradeep Ravikumar. [doi]
• Learning Guidance Rewards with Trajectory-space SmoothingTanmay Gangwani, Yuan Zhou 0007, Jian Peng 0001. [doi]
• High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian OptimizationQing Feng, Benjamin Letham, Hongzi Mao, Eytan Bakshy. [doi]
• Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep LearningJulius Berner, Markus Dablander, Philipp Grohs. [doi]
• Towards Neural Programming InterfacesZachary Brown 0001, Nathaniel Robinson, David Wingate, Nancy Fulda. [doi]
• Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-SobolevXiao Wang, Qi Lei, Ioannis Panageas. [doi]
• Model Inversion Networks for Model-Based OptimizationAviral Kumar, Sergey Levine. [doi]
• Spectral Temporal Graph Neural Network for Multivariate Time-series ForecastingDefu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Congrui Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang. [doi]
• Implicit Regularization in Deep Learning May Not Be Explainable by NormsNoam Razin, Nadav Cohen. [doi]
• Learning from Aggregate ObservationsYivan Zhang, Nontawat Charoenphakdee, Zhenguo Wu, Masashi Sugiyama. [doi]
• OrganITE: Optimal transplant donor organ offering using an individual treatment effectJeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar. [doi]
• Training Linear Finite-State MachinesArash Ardakani, Amir Ardakani, Warren J. Gross. [doi]
• From Predictions to Decisions: Using Lookahead RegularizationNir Rosenfeld, Anna Hilgard, Sai Srivatsa Ravindranath, David C. Parkes. [doi]
• Self-Adaptively Learning to Demoiré from Focused and Defocused Image PairsLin Liu, Shanxin Yuan, Jianzhuang Liu, Liping Bao, Gregory G. Slabaugh, Qi Tian. [doi]
• Graph Contrastive Learning with AugmentationsYuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen. [doi]
• Linear-Sample Learning of Low-Rank DistributionsAyush Jain, Alon Orlitsky. [doi]
• Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural NetworksWenrui Zhang, Peng Li 0001. [doi]
• Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average RewardGuannan Qu, Yiheng Lin, Adam Wierman, Na Li 0002. [doi]
• Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin AlgorithmAdil Salim, Peter Richtárik. [doi]
• FrugalML: How to use ML Prediction APIs more accurately and cheaplyLingjiao Chen, Matei Zaharia, James Y. Zou. [doi]
• A/B Testing in Dense Large-Scale Networks: Design and InferencePreetam Nandy, Kinjal Basu 0001, Shaunak Chatterjee, Ye Tu. [doi]
• Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample ComplexitySimon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang. [doi]
• Emergent Complexity and Zero-shot Transfer via Unsupervised Environment DesignMichael Dennis 0001, Natasha Jaques, Eugene Vinitsky, Alexandre M. Bayen, Stuart Russell, Andrew Critch, Sergey Levine. [doi]
• Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement LearningTabish Rashid, Gregory Farquhar, Bei Peng, Shimon Whiteson. [doi]
• Identifying Mislabeled Data using the Area Under the Margin RankingGeoff Pleiss, Tianyi Zhang 0007, Ethan R. Elenberg, Kilian Q. Weinberger. [doi]
• BoxE: A Box Embedding Model for Knowledge Base CompletionRalph Abboud, Ismail Ilkan Ceylan, Thomas Lukasiewicz, Tommaso Salvatori. [doi]
• Testing Determinantal Point ProcessesKhashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka. [doi]
• HRN: A Holistic Approach to One Class LearningWenpeng Hu, Mengyu Wang, Qi Qin, Jinwen Ma, Bing Liu 0001. [doi]
• Unsupervised Learning of Dense Visual RepresentationsPedro O. Pinheiro, Amjad Almahairi, Ryan Y. Benmalek, Florian Golemo, Aaron C. Courville. [doi]
• Probabilistic Active Meta-LearningJean Kaddour, Steindór Sæmundsson, Marc Peter Deisenroth. [doi]
• Coupling-based Invertible Neural Networks Are Universal Diffeomorphism ApproximatorsTakeshi Teshima, Isao Ishikawa, Koichi Tojo, Kenta Oono, Masahiro Ikeda, Masashi Sugiyama. [doi]
• Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta LearningYifan Hu, Siqi Zhang, Xin Chen, Niao He. [doi]
• Bayesian Meta-Learning for the Few-Shot Setting via Deep KernelsMassimiliano Patacchiola, Jack Turner, Elliot J. Crowley, Michael F. P. O'Boyle, Amos J. Storkey. [doi]
• AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing FlowsHadi Mohaghegh Dolatabadi, Sarah M. Erfani, Christopher Leckie. [doi]
• On Adaptive Distance EstimationYeshwanth Cherapanamjeri, Jelani Nelson. [doi]
• Agnostic Learning with Multiple ObjectivesCorinna Cortes, Mehryar Mohri, Javier Gonzalvo, Dmitry Storcheus. [doi]
• On the Tightness of Semidefinite Relaxations for Certifying Robustness to Adversarial ExamplesRichard Y. Zhang. [doi]
• Avoiding Side Effects By Considering Future TasksVictoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg. [doi]
• Interstellar: Searching Recurrent Architecture for Knowledge Graph EmbeddingYongqi Zhang, Quanming Yao, Lei Chen 0002. [doi]
• Certified Defense to Image Transformations via Randomized SmoothingMarc Fischer, Maximilian Baader, Martin T. Vechev. [doi]
• Uncertainty Aware Semi-Supervised Learning on Graph DataXujiang Zhao, Feng Chen 0001, Shu Hu, Jin-Hee Cho. [doi]
• ColdGANs: Taming Language GANs with Cautious Sampling StrategiesThomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano. [doi]
• Adversarial Sparse Transformer for Time Series ForecastingSifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei 0001, JunZhou Huang. [doi]
• Deep Structural Causal Models for Tractable Counterfactual InferenceNick Pawlowski, Daniel Coelho de Castro, Ben Glocker. [doi]
• Tight last-iterate convergence rates for no-regret learning in multi-player gamesNoah Golowich, Sarath Pattathil, Constantinos Daskalakis. [doi]
• OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and ClassificationTaewon Jeong, Heeyoung Kim. [doi]
• Learning compositional functions via multiplicative weight updatesJeremy Bernstein, Jiawei Zhao, Markus Meister, Ming-Yu Liu 0001, Anima Anandkumar, Yisong Yue. [doi]
• Model Fusion via Optimal TransportSidak Pal Singh, Martin Jaggi. [doi]
• Adaptive Gradient Quantization for Data-Parallel SGDFartash Faghri, Iman Tabrizian, Ilia Markov, Dan Alistarh, Daniel M. Roy 0001, Ali Ramezani-Kebrya. [doi]
• Rescuing neural spike train models from bad MLEDiego M. Arribas, Yuan Zhao 0004, Il Memming Park. [doi]
• Graph Information BottleneckTailin Wu, Hongyu Ren, Pan Li, Jure Leskovec. [doi]
• MPNet: Masked and Permuted Pre-training for Language UnderstandingKaitao Song, Xu Tan 0003, Tao Qin, Jianfeng Lu, Tie-Yan Liu. [doi]
• Learning to Prove Theorems by Learning to Generate TheoremsMingzhe Wang, Jia Deng. [doi]
• Cooperative Heterogeneous Deep Reinforcement LearningHan Zheng, Pengfei Wei, Jing Jiang 0002, Guodong Long, Qinghua Lu 0001, Chengqi Zhang. [doi]
• Most ReLU Networks Suffer from $\ell^2$ Adversarial PerturbationsAmit Daniely, Hadas Shacham. [doi]
• Neural Bridge Sampling for Evaluating Safety-Critical Autonomous SystemsAman Sinha, Matthew O'Kelly, Russ Tedrake, John C. Duchi. [doi]
• Decentralized Langevin Dynamics for Bayesian LearningAnjaly Parayil, He Bai, Jemin George, Prudhvi Gurram. [doi]
• Diversity can be Transferred: Output Diversification for White- and Black-box AttacksYusuke Tashiro, Yang Song 0011, Stefano Ermon. [doi]
• Video Frame Interpolation without Temporal PriorsYoujian Zhang, Chaoyue Wang, Dacheng Tao. [doi]
• POMDPs in Continuous Time and Discrete SpacesBastian Alt, Matthias Schultheis, Heinz Koeppl. [doi]
• Simple and Fast Algorithm for Binary Integer and Online Linear ProgrammingXiaocheng Li, Chunlin Sun, Yinyu Ye. [doi]
• Direct Feedback Alignment Scales to Modern Deep Learning Tasks and ArchitecturesJulien Launay, Iacopo Poli, François Boniface, Florent Krzakala. [doi]
• Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single SampleShir Gur, Sagie Benaim, Lior Wolf. [doi]
• Learning Differentiable Programs with Admissible Neural HeuristicsAmeesh Shah, Eric Zhan, Jennifer J. Sun, Abhinav Verma, Yisong Yue, Swarat Chaudhuri. [doi]
• Optimal Private Median Estimation under Minimal Distributional AssumptionsChristos Tzamos, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ilias Zadik. [doi]
• RandAugment: Practical Automated Data Augmentation with a Reduced Search SpaceEkin Dogus Cubuk, Barret Zoph, Jon Shlens, Quoc Le 0001. [doi]
• Rethinking the Value of Labels for Improving Class-Imbalanced LearningYuzhe Yang, Zhi Xu. [doi]
• Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision ProcessesDongsheng Ding, Kaiqing Zhang, Tamer Basar, Mihailo R. Jovanovic. [doi]
• Tensor Completion Made PracticalAllen Liu, Ankur Moitra. [doi]
• Modeling Noisy Annotations for Crowd CountingJia Wan, Antoni B. Chan. [doi]
• Optimizing Neural Networks via Koopman Operator TheoryAkshunna S. Dogra, William T. Redman. [doi]
• CLEARER: Multi-Scale Neural Architecture Search for Image RestorationYuanbiao Gou, Boyun Li, Zitao Liu, Songfan Yang, Xi Peng 0001. [doi]
• Decision trees as partitioning machines to characterize their generalization propertiesJean-Samuel Leboeuf, Frédéric Leblanc, Mario Marchand. [doi]
• Representation Learning for Integrating Multi-domain Outcomes to Optimize Individualized TreatmentYuan Chen, Donglin Zeng, Tianchen Xu, Yuanjia Wang. [doi]
• Learning from Label Proportions: A Mutual Contamination FrameworkClayton Scott, Jianxin Zhang. [doi]
• Robust Deep Reinforcement Learning against Adversarial Perturbations on State ObservationsHuan Zhang 0001, Hongge Chen, Chaowei Xiao, Bo Li 0026, Mingyan Liu, Duane S. Boning, Cho-Jui Hsieh. [doi]
• Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear ModelRaphaël Berthier, Francis R. Bach, Pierre Gaillard. [doi]
• COOT: Cooperative Hierarchical Transformer for Video-Text Representation LearningSimon Ging, Mohammadreza Zolfaghari, Hamed Pirsiavash, Thomas Brox. [doi]
• Model Selection for Production System via Automated Online ExperimentsZhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Benjamin A. Carterette, Mounia Lalmas. [doi]
• H-Mem: Harnessing synaptic plasticity with Hebbian Memory NetworksThomas Limbacher, Robert A. Legenstein. [doi]
• A Combinatorial Perspective on Transfer LearningJianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness. [doi]
• Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk EstimationUchenna Akujuobi, Jun Chen, Mohamed Elhoseiny, Michael Spranger, Xiangliang Zhang 0001. [doi]
• MetaSDF: Meta-Learning Signed Distance FunctionsVincent Sitzmann, Eric R. Chan, Richard Tucker, Noah Snavely, Gordon Wetzstein. [doi]
• Hedging in games: Faster convergence of external and swap regretsXi Chen, Binghui Peng. [doi]
• GPU-Accelerated Primal Learning for Extremely Fast Large-Scale ClassificationJohn T. Halloran, David M. Rocke. [doi]
• Distribution Matching for Crowd CountingBoyu Wang 0001, Huidong Liu, Dimitris Samaras, Minh Hoai Nguyen. [doi]
• Achieving Equalized Odds by Resampling Sensitive AttributesYaniv Romano, Stephen Bates, Emmanuel J. Candès. [doi]
• Deep Evidential RegressionAlexander Amini, Wilko Schwarting, Ava Soleimany, Daniela Rus. [doi]
• Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten PackingArun Jambulapati, Jerry Li 0001, Kevin Tian. [doi]
• Unsupervised object-centric video generation and decomposition in 3DPaul Henderson, Christoph H. Lampert. [doi]
• Weakly-Supervised Reinforcement Learning for Controllable BehaviorLisa Lee, Ben Eysenbach, Russ R. Salakhutdinov, Shixiang Shane Gu, Chelsea Finn. [doi]
• Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance ReductionGen Li 0005, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen 0002. [doi]
• The Adaptive Complexity of Maximizing a Gross Substitutes ValuationRon Kupfer, Sharon Qian, Eric Balkanski, Yaron Singer. [doi]
• Simple and Scalable Sparse k-means Clustering via Feature RankingZhiyue Zhang, Kenneth Lange, Jason Xu. [doi]
• ConvBERT: Improving BERT with Span-based Dynamic ConvolutionZihang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan. [doi]
• Bias no more: high-probability data-dependent regret bounds for adversarial bandits and MDPsChung-wei Lee, Haipeng Luo, Chen-Yu Wei, Mengxiao Zhang. [doi]
• Random Reshuffling is Not Always BetterChristopher De Sa. [doi]
• (De)Randomized Smoothing for Certifiable Defense against Patch AttacksAlexander Levine 0001, Soheil Feizi. [doi]
• Sparse Spectrum Warped Input Measures for Nonstationary Kernel LearningAnthony Tompkins, Rafael Oliveira 0001, Fabio T. Ramos. [doi]
• AViD Dataset: Anonymized Videos from Diverse CountriesA. J. Piergiovanni, Michael S. Ryoo. [doi]
• A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal DistributionsWei Deng, Guang Lin, Faming Liang. [doi]
• Counterfactual Vision-and-Language Navigation: Unravelling the UnseenAmin Parvaneh, Ehsan Abbasnejad, Damien Teney, Qinfeng Shi, Anton van den Hengel. [doi]
• Cascaded Text Generation with Markov TransformersYuntian Deng, Alexander M. Rush. [doi]
• Generalization Bound of Gradient Descent for Non-Convex Metric LearningMingzhi Dong, Xiaochen Yang, Rui Zhu 0006, Yujiang Wang 0001, Jing-Hao Xue. [doi]
• Comparator-Adaptive Convex BanditsDirk van der Hoeven, Ashok Cutkosky, Haipeng Luo. [doi]
• Statistical Guarantees of Distributed Nearest Neighbor ClassificationJiexin Duan, Xingye Qiao, Guang Cheng. [doi]
• Towards Problem-dependent Optimal Learning RatesYunbei Xu, Assaf Zeevi. [doi]
• Position-based Scaled Gradient for Model Quantization and PruningJangho Kim, KiYoon Yoo, Nojun Kwak. [doi]
• From Finite to Countable-Armed BanditsAnand Kalvit, Assaf Zeevi. [doi]
• Optimal Iterative Sketching Methods with the Subsampled Randomized Hadamard TransformJonathan Lacotte, SiFan Liu, Edgar Dobriban, Mert Pilanci. [doi]
• Reliable Graph Neural Networks via Robust AggregationSimon Geisler, Daniel Zügner, Stephan Günnemann. [doi]
• Sanity-Checking Pruning Methods: Random Tickets can Win the JackpotJingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, RuiQi Gao, Liwei Wang 0001, Jason D. Lee. [doi]
• Weakly Supervised Deep Functional Maps for Shape MatchingAbhishek Sharma, Maks Ovsjanikov. [doi]
• Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and OptimizationAbhinav Agrawal 0001, Daniel R. Sheldon, Justin Domke. [doi]
• Matrix Completion with Quantified Uncertainty through Low Rank Gaussian CopulaYuxuan Zhao, Madeleine Udell. [doi]
• Learning to Mutate with Hypergradient Guided PopulationZhiqiang Tao, Yaliang Li, Bolin Ding, Ce Zhang, Jingren Zhou, Yun Fu 0001. [doi]
• Content Provider Dynamics and Coordination in Recommendation EcosystemsOmer Ben-Porat, Itay Rosenberg, Moshe Tennenholtz. [doi]
• Meta-Consolidation for Continual LearningK. J. Joseph, Vineeth Nallure Balasubramanian. [doi]
• Energy-based Out-of-distribution DetectionWeitang Liu, Xiaoyun Wang, John D. Owens, Yixuan Li. [doi]
• Neural Power UnitsNiklas Heim, Tomás Pevný, Vásek Smídl. [doi]
• Optimally Deceiving a Learning Leader in Stackelberg GamesGeorgios Birmpas, Jiarui Gan, Alexandros Hollender, Francisco J. Marmolejo Cossío, Ninad Rajgopal, Alexandros A. Voudouris. [doi]
• Top-KAST: Top-K Always Sparse TrainingSiddhant M. Jayakumar, Razvan Pascanu, Jack W. Rae, Simon Osindero, Erich Elsen. [doi]
• Lower Bounds and Optimal Algorithms for Personalized Federated LearningFilip Hanzely, Slavomír Hanzely, Samuel Horváth, Peter Richtárik. [doi]
• CogLTX: Applying BERT to Long TextsMing Ding, Chang Zhou, Hongxia Yang, Jie Tang 0001. [doi]
• Improved Analysis of Clipping Algorithms for Non-convex OptimizationBohang Zhang, Jikai Jin, Cong Fang, Liwei Wang. [doi]
• Multi-task Batch Reinforcement Learning with Metric LearningJiachen Li, Quan Vuong, Shuang Liu, Minghua Liu, Kamil Ciosek, Henrik I. Christensen, Hao Su 0001. [doi]
• A Catalyst Framework for Minimax OptimizationJunchi Yang, Siqi Zhang, Negar Kiyavash, Niao He. [doi]
• FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN TrainingYonggan Fu, Haoran You, Yang Zhao, Yue Wang 0036, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin. [doi]
• Learning Sparse Prototypes for Text GenerationJunxian He, Taylor Berg-Kirkpatrick, Graham Neubig. [doi]
• CoMIR: Contrastive Multimodal Image Representation for RegistrationNicolas Pielawski, Elisabeth Wetzer, Johan Öfverstedt, Jiahao Lu, Carolina Wählby, Joakim Lindblad, Natasa Sladoje. [doi]
• BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement LearningXinyue Chen, Zijian Zhou, Zheng Wang, Che Wang, Yanqiu Wu, Keith Ross. [doi]
• Robust Density Estimation under Besov IPM LossesAnanya Uppal, Shashank Singh 0005, Barnabás Póczos. [doi]
• Attention-Gated Brain Propagation: How the brain can implement reward-based error backpropagationIsabella Pozzi, Sander M. Bohté, Pieter R. Roelfsema. [doi]
• Cross-lingual Retrieval for Iterative Self-Supervised TrainingChau Tran, Yuqing Tang, Xian Li, Jiatao Gu. [doi]
• A Study on Encodings for Neural Architecture SearchColin White, Willie Neiswanger, Sam Nolen, Yash Savani. [doi]
• Improved Algorithms for Online Submodular Maximization via First-order Regret BoundsNicholas J. A. Harvey, Christopher Liaw, Tasuku Soma. [doi]
• Bidirectional Convolutional Poisson Gamma Dynamical SystemsWenchao Chen, Chaojie Wang, Bo Chen 0001, Yicheng Liu, Hao Zhang 0050, Mingyuan Zhou. [doi]
• General Control Functions for Causal Effect Estimation from IVsAahlad Manas Puli, Rajesh Ranganath. [doi]
• Learning from Failure: De-biasing Classifier from Biased ClassifierJun Hyun Nam, Hyuntak Cha, Sungsoo Ahn, Jaeho Lee, Jinwoo Shin. [doi]
• Learning with Operator-valued Kernels in Reproducing Kernel Krein SpacesAkash Saha, Balamurugan Palaniappan. [doi]
• Learning Object-Centric Representations of Multi-Object Scenes from Multiple ViewsNanbo Li, Cian Eastwood, Robert B. Fisher. [doi]
• Improved Guarantees for k-means++ and k-means++ ParallelKonstantin Makarychev, Aravind Reddy, Liren Shan. [doi]
• Directional Pruning of Deep Neural NetworksShih-Kang Chao, Zhanyu Wang, Yue Xing, Guang Cheng. [doi]
• AutoPrivacy: Automated Layer-wise Parameter Selection for Secure Neural Network InferenceQian Lou, Bian Song, Lei Jiang 0001. [doi]
• Wisdom of the Ensemble: Improving Consistency of Deep Learning ModelsLijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta 0001, Jiangzhuo Chen, Madhav Marathe. [doi]
• Learning Invariances in Neural Networks from Training DataGregory W. Benton, Marc Finzi, Pavel Izmailov, Andrew Gordon Wilson. [doi]
• Discriminative Sounding Objects Localization via Self-supervised Audiovisual MatchingDi Hu, Rui Qian, Minyue Jiang, Xiao Tan, Shilei Wen, Errui Ding, Weiyao Lin, Dejing Dou. [doi]
• Neural Networks Learning and Memorization with (almost) no Over-ParameterizationAmit Daniely. [doi]
• Higher-Order Spectral Clustering of Directed GraphsSteinar Laenen, He Sun. [doi]
• Adaptive Importance Sampling for Finite-Sum Optimization and Sampling with Decreasing Step-SizesAyoub El Hanchi, David Stephens. [doi]
• Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object DetectionXiang Li 0041, Wenhai Wang, Lijun Wu, Shuo Chen 0003, Xiaolin Hu 0001, Jun Li, Jinhui Tang, Jian Yang 0003. [doi]
• Movement Pruning: Adaptive Sparsity by Fine-TuningVictor Sanh, Thomas Wolf 0008, Alexander M. Rush. [doi]
• Neural Networks with Recurrent Generative FeedbackYujia Huang, James Gornet, Sihui Dai, Zhiding Yu, Tan M. Nguyen, Doris Y. Tsao, Anima Anandkumar. [doi]
• Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial LossShuang Qiu, Xiaohan Wei, Zhuoran Yang, Jieping Ye, Zhaoran Wang. [doi]
• Online Planning with Lookahead PoliciesYonathan Efroni, Mohammad Ghavamzadeh, Shie Mannor. [doi]
• Interferobot: aligning an optical interferometer by a reinforcement learning agentDmitry Sorokin, Alexander Ulanov, Ekaterina Sazhina, Alexander Lvovsky. [doi]
• Practical Low-Rank Communication Compression in Decentralized Deep LearningThijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi. [doi]
• Distributional Robustness with IPMs and links to Regularization and GANsHisham Husain. [doi]
• UCLID-Net: Single View Reconstruction in Object SpaceBenoît Guillard, Edoardo Remelli, Pascal Fua. [doi]
• Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual LearningMassimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, Laurent Charlin. [doi]
• Balanced Meta-Softmax for Long-Tailed Visual RecognitionJiawei Ren, Cunjun Yu, Shunan Sheng, Xiao Ma, Haiyu Zhao, Shuai Yi, Hongsheng Li. [doi]
• Submodular Maximization Through Barrier FunctionsAshwinkumar Badanidiyuru, Amin Karbasi, Ehsan Kazemi 0001, Jan Vondrák. [doi]
• Glance and Focus: a Dynamic Approach to Reducing Spatial Redundancy in Image ClassificationYulin Wang, Kangchen Lv, Rui Huang, Shiji Song, Le Yang, Gao Huang. [doi]
• Why Normalizing Flows Fail to Detect Out-of-Distribution DataPolina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson. [doi]
• Digraph Inception Convolutional NetworksZekun Tong, Yuxuan Liang, Changsheng Sun, Xinke Li, David S. Rosenblum, Andrew Lim 0001. [doi]
• Regularizing Black-box Models for Improved InterpretabilityGregory Plumb, Maruan Al-Shedivat, Ángel Alexander Cabrera, Adam Perer, Eric P. Xing, Ameet Talwalkar. [doi]
• Dynamic Regret of Convex and Smooth FunctionsPeng Zhao 0006, Yu-Jie Zhang, Lijun Zhang, Zhi-Hua Zhou. [doi]
• Calibration of Shared Equilibria in General Sum Partially Observable Markov GamesNelson Vadori, Sumitra Ganesh, Prashant P. Reddy, Manuela Veloso. [doi]
• Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?Guoqiang Wu, Jun Zhu. [doi]
• On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex ProblemsPanayotis Mertikopoulos, Nadav Hallak, Ali Kavis, Volkan Cevher. [doi]
• Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast GradientsWilliam S. Moses, Valentin Churavy. [doi]
• Skeleton-bridged Point Completion: From Global Inference to Local AdjustmentYinyu Nie, Yiqun Lin, Xiaoguang Han, Shihui Guo, Jian Chang, Shuguang Cui, Jian J. Zhang 0001. [doi]
• Continual Learning of Control Primitives : Skill Discovery via Reset-GamesKelvin Xu, Siddharth Verma, Chelsea Finn, Sergey Levine. [doi]
• Privacy Amplification via Random Check-InsBorja Balle, Peter Kairouz, Brendan McMahan, Om Dipakbhai Thakkar, Abhradeep Thakurta. [doi]
• Learning Continuous System Dynamics from Irregularly-Sampled Partial ObservationsZijie Huang, Yizhou Sun, Wei Wang 0010. [doi]
• Estimating Fluctuations in Neural Representations of Uncertain EnvironmentsSahand Farhoodi, Mark Plitt, Lisa M. Giocomo, Uri T. Eden. [doi]
• An Improved Analysis of Stochastic Gradient Descent with MomentumYanli Liu 0003, Yuan Gao, Wotao Yin. [doi]
• The Complete Lasso Tradeoff DiagramHua Wang, Yachong Yang, Zhiqi Bu, Weijie J. Su. [doi]
• Transferable Graph Optimizers for ML CompilersYanqi Zhou, Sudip Roy 0002, AmirAli Abdolrashidi, Daniel Wong 0001, Peter C. Ma, Qiumin Xu, Hanxiao Liu, Mangpo Phitchaya Phothilimtha, Shen Wang, Anna Goldie, Azalia Mirhoseini, James Laudon. [doi]
• Matrix Completion with Hierarchical Graph Side InformationAdel M. Elmahdy, Junhyung Ahn, Changho Suh, Soheil Mohajer. [doi]
• Interpolation Technique to Speed Up Gradients Propagation in Neural ODEsTalgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets. [doi]
• Revisiting Parameter Sharing for Automatic Neural Channel Number SearchJiaxing Wang, Haoli Bai, Jiaxiang Wu, Xupeng Shi, JunZhou Huang, Irwin King, Michael R. Lyu, Jian Cheng 0001. [doi]
• Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate ReductionYaodong Yu, Kwan Ho Ryan Chan, Chong You, Chaobing Song, Yi Ma. [doi]
• Online Algorithms for Multi-shop Ski Rental with Machine Learned AdviceShufan Wang, Jian Li, Shiqiang Wang. [doi]
• Latent Template Induction with Gumbel-CRFsYao Fu, Chuanqi Tan, Bin Bi, Mosha Chen, Yansong Feng, Alexander M. Rush. [doi]
• Hitting the High Notes: Subset Selection for Maximizing Expected Order StatisticsAranyak Mehta, Uri Nadav, Alexandros Psomas, Aviad Rubinstein. [doi]
• Byzantine Resilient Distributed Multi-Task LearningJiani Li, Waseem Abbas, Xenofon D. Koutsoukos. [doi]
• In search of robust measures of generalizationGintare Karolina Dziugaite, Alexandre Drouin, Brady Neal, Nitarshan Rajkumar, Ethan Caballero, Linbo Wang, Ioannis Mitliagkas, Daniel M. Roy 0001. [doi]
• Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical ModelsAdarsh K. Jeewajee, Leslie Pack Kaelbling. [doi]
• Differentiable Augmentation for Data-Efficient GAN TrainingShengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, Song Han 0003. [doi]
• Delay and Cooperation in Nonstochastic Linear BanditsShinji Ito, Daisuke Hatano, Hanna Sumita, Kei Takemura, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi. [doi]
• The route to chaos in routing games: When is price of anarchy too optimistic?Thiparat Chotibut, Fryderyk Falniowski, Michal Misiurewicz, Georgios Piliouras. [doi]
• Unfolding recurrence by Green's functions for optimized reservoir computingSandra Nestler, Christian Keup, David Dahmen, Matthieu Gilson, Holger Rauhut, Moritz Helias. [doi]
• Incorporating BERT into Parallel Sequence Decoding with AdaptersJunliang Guo, Zhirui Zhang, Linli Xu, Hao-Ran Wei, Boxing Chen, Enhong Chen. [doi]
• Demixed shared component analysis of neural population data from multiple brain areasYu Takagi, Steven W. Kennerley, Jun-ichiro Hirayama, Laurence T. Hunt. [doi]
• NeuMiss networks: differentiable programming for supervised learning with missing valuesMarine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux. [doi]
• Domain Adaptation as a Problem of Inference on Graphical ModelsKun Zhang 0001, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, Clark Glymour. [doi]
• Flows for simultaneous manifold learning and density estimationJohann Brehmer, Kyle Cranmer. [doi]
• Curriculum By SmoothingSamarth Sinha, Animesh Garg, Hugo Larochelle. [doi]
• Planning with General Objective Functions: Going Beyond Total RewardsRuosong Wang, Peilin Zhong, Simon S. Du, Russ R. Salakhutdinov, Lin F. Yang. [doi]
• Phase retrieval in high dimensions: Statistical and computational phase transitionsAntoine Maillard, Bruno Loureiro, Florent Krzakala, Lenka Zdeborová. [doi]
• A Decentralized Parallel Algorithm for Training Generative Adversarial NetsMingrui Liu, Wei Zhang 0022, Youssef Mroueh, Xiaodong Cui, Jarret Ross, Tianbao Yang, Payel Das. [doi]
• Linearly Converging Error Compensated SGDEduard A. Gorbunov, Dmitry Kovalev, Dmitry Makarenko, Peter Richtárik. [doi]
• Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic ProgrammingVo Nguyen Le Duy, Hiroki Toda, Ryota Sugiyama, Ichiro Takeuchi. [doi]
• Trading Personalization for Accuracy: Data Debugging in Collaborative FilteringLong Chen, Yuan Yao 0001, Feng Xu 0007, Miao Xu, Hanghang Tong. [doi]
• Self-Supervised Generative Adversarial CompressionChong Yu, Jeff Pool. [doi]
• Quantifying Learnability and Describability of Visual Concepts Emerging in Representation LearningIro Laina, Ruth Fong, Andrea Vedaldi. [doi]
• Continuous Surface EmbeddingsNatalia Neverova, David Novotný, Marc Szafraniec, Vasil Khalidov, Patrick Labatut, Andrea Vedaldi. [doi]
• Smooth And Consistent Probabilistic Regression TreesSami Alkhoury, Emilie Devijver, Marianne Clausel, Myriam Tami, Éric Gaussier, Georges Oppenheim. [doi]
• How does Weight Correlation Affect Generalisation Ability of Deep Neural Networks?Gaojie Jin, Xinping Yi, Liang Zhang, Lijun Zhang 0001, Sven Schewe, Xiaowei Huang 0001. [doi]
• Permute-and-Flip: A new mechanism for differentially private selectionRyan Mckenna, Daniel R. Sheldon. [doi]
• Knowledge Augmented Deep Neural Networks for Joint Facial Expression and Action Unit RecognitionZijun Cui, Tengfei Song, Yuru Wang, Qiang Ji. [doi]
• ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed TrainingChia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan. [doi]
• Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian NetworksJunsouk Choi, Robert S. Chapkin, Yang Ni. [doi]
• The Origins and Prevalence of Texture Bias in Convolutional Neural NetworksKatherine L. Hermann, Ting Chen, Simon Kornblith. [doi]
• Myersonian RegressionAllen Liu, Renato Paes Leme, Jon Schneider. [doi]
• Variational Bayesian UnlearningQuoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet. [doi]
• Semi-Supervised Neural Architecture SearchRenqian Luo, Xu Tan 0003, Rui Wang, Tao Qin, Enhong Chen, Tie-Yan Liu. [doi]
• Differentially-Private Federated Linear BanditsAbhimanyu Dubey, Alex 'Sandy' Pentland. [doi]
• Hard Shape-Constrained Kernel MachinesPierre-Cyril Aubin-Frankowski, Zoltán Szabó 0001. [doi]
• Neural Topographic Factor Analysis for fMRI DataEli Sennesh, Zulqarnain Khan, Yiyu Wang, J. Benjamin Hutchinson, Ajay B. Satpute, Jennifer G. Dy, Jan-Willem van de Meent. [doi]
• A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural networkBasile Confavreux, Friedemann Zenke, Everton J. Agnes, Timothy P. Lillicrap, Tim P. Vogels. [doi]
• On the Convergence of Smooth Regularized Approximate Value Iteration SchemesElena Smirnova, Elvis Dohmatob. [doi]
• The Power of Predictions in Online ControlChenkai Yu, Guanya Shi, Soon Jo Chung, Yisong Yue, Adam Wierman. [doi]
• Path Integral Based Convolution and Pooling for Graph Neural NetworksZheng Ma, Junyu Xuan, Yu Guang Wang 0001, Ming Li, Pietro Liò. [doi]
• Self-Supervised Graph Transformer on Large-Scale Molecular DataYu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei 0001, Wenbing Huang, JunZhou Huang. [doi]
• Meta-Learning through Hebbian Plasticity in Random NetworksElias Najarro, Sebastian Risi. [doi]
• Guided Adversarial Attack for Evaluating and Enhancing Adversarial DefensesGaurang Sriramanan, Sravanti Addepalli, Arya Baburaj, Venkatesh Babu R.. [doi]
• Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor NetworksJing Xu, Fangwei Zhong, Yizhou Wang 0001. [doi]
• Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic SegmentationKwanYong Park, Sanghyun Woo, Inkyu Shin, In-So Kweon. [doi]
• Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-CountsBertrand Charpentier, Daniel Zügner, Stephan Günnemann. [doi]
• Optimal visual search based on a model of target detectability in natural imagesShima Rashidi, Krista A. Ehinger, Andrew Turpin, Lars Kulik. [doi]
• Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal EffectKaihua Tang, Jianqiang Huang, Hanwang Zhang. [doi]
• Model Agnostic Multilevel ExplanationsKarthikeyan Natesan Ramamurthy, Bhanukiran Vinzamuri, Yunfeng Zhang, Amit Dhurandhar. [doi]
• Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of SymmetryYossi Arjevani, Michael Field. [doi]
• CoinDICE: Off-Policy Confidence Interval EstimationBo Dai, Ofir Nachum, Yinlam Chow, Lihong Li 0001, Csaba Szepesvári, Dale Schuurmans. [doi]
• Smoothly Bounding User Contributions in Differential PrivacyAlessandro Epasto, Mohammad Mahdian, Jieming Mao, Vahab S. Mirrokni, Lijie Ren. [doi]
• DisCor: Corrective Feedback in Reinforcement Learning via Distribution CorrectionAviral Kumar, Abhishek Gupta 0004, Sergey Levine. [doi]
• Intra Order-preserving Functions for Calibration of Multi-Class Neural NetworksAmir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley 0001, Byron Boots. [doi]
• Fighting Copycat Agents in Behavioral Cloning from Observation HistoriesChuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao 0029. [doi]
• Identifying Causal-Effect Inference Failure with Uncertainty-Aware ModelsAndrew Jesson, Sören Mindermann, Uri Shalit, Yarin Gal. [doi]
• Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep NetworksSoham De, Samuel L. Smith. [doi]
• On the Trade-off between Adversarial and Backdoor RobustnessCheng-Hsin Weng, Yan-Ting Lee, Shan-Hung Wu. [doi]
• Attack of the Tails: Yes, You Really Can Backdoor Federated LearningHongyi Wang, Kartik Sreenivasan, Shashank Rajput, Harit Vishwakarma, Saurabh Agarwal, Jy-yong Sohn, Kangwook Lee, Dimitris S. Papailiopoulos. [doi]
• Improving Sample Complexity Bounds for (Natural) Actor-Critic AlgorithmsTengyu Xu, Zhe Wang, Yingbin Liang. [doi]
• Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case StudyAssaf Dauber, Meir Feder, Tomer Koren, Roi Livni. [doi]
• Practical Quasi-Newton Methods for Training Deep Neural NetworksDonald Goldfarb, Yi Ren, Achraf Bahamou. [doi]
• Variance Reduction via Accelerated Dual Averaging for Finite-Sum OptimizationChaobing Song, Yong Jiang, Yi Ma. [doi]
• Learning to Incentivize Other Learning AgentsJiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes 0001, Hongyuan Zha. [doi]
• SCOP: Scientific Control for Reliable Neural Network PruningYehui Tang, Yunhe Wang, Yixing Xu, Dacheng Tao, Chunjing Xu, Chao Xu 0006, Chang Xu 0002. [doi]
• Walsh-Hadamard Variational Inference for Bayesian Deep LearningSimone Rossi, Sébastien Marmin, Maurizio Filippone. [doi]
• Wavelet Flow: Fast Training of High Resolution Normalizing FlowsJason J. Yu, Konstantinos G. Derpanis, Marcus A. Brubaker. [doi]
• Causal Discovery in Physical Systems from VideosYunzhu Li, Antonio Torralba 0001, Anima Anandkumar, Dieter Fox, Animesh Garg. [doi]
• When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian ProcessesZhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar. [doi]
• On 1/n neural representation and robustnessJosue Nassar, Piotr A. Sokól, SueYeon Chung, Kenneth D. Harris, Il Memming Park. [doi]
• LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh RegistrationBharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt, Gerard Pons-Moll. [doi]
• A causal view of compositional zero-shot recognitionYuval Atzmon, Felix Kreuk, Uri Shalit, Gal Chechik. [doi]
• Model-based Policy Optimization with Unsupervised Model AdaptationJian Shen 0003, Han Zhao 0002, Weinan Zhang 0001, Yong Yu 0001. [doi]
• Fairness without Demographics through Adversarially Reweighted LearningPreethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang 0002, Ed Chi. [doi]
• Exponential ergodicity of mirror-Langevin diffusionsSinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin Stromme. [doi]
• Online Influence Maximization under Linear Threshold ModelShuai Li, Fang Kong, Kejie Tang, Qizhi Li, Wei Chen. [doi]
• Efficient Contextual Bandits with Continuous ActionsMaryam Majzoubi, Chicheng Zhang, Rajan Chari, Akshay Krishnamurthy, John Langford 0001, Aleksandrs Slivkins. [doi]
• Factor Graph GrammarsDavid Chiang 0001, Darcey Riley. [doi]
• Learning Invariants through Soft UnificationNuri Cingillioglu, Alessandra Russo. [doi]
• Rankmax: An Adaptive Projection Alternative to the Softmax FunctionWeiwei Kong, Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang. [doi]
• Language as a Cognitive Tool to Imagine Goals in Curiosity Driven ExplorationCédric Colas, Tristan Karch, Nicolas Lair, Jean-Michel Dussoux, Clément Moulin-Frier, Peter F. Dominey, Pierre-Yves Oudeyer. [doi]
• AvE: Assistance via EmpowermentYuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan. [doi]
• Bootstrap Your Own Latent - A New Approach to Self-Supervised LearningJean-Bastien grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H. Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Ávila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, Rémi Munos, Michal Valko. [doi]
• Robust Recursive Partitioning for Heterogeneous Treatment Effects with Uncertainty QuantificationHyun Suk Lee, Yao Zhang, William R. Zame, Cong Shen, Jang-Won Lee, Mihaela van der Schaar. [doi]
• Preference learning along multiple criteria: A game-theoretic perspectiveKush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright. [doi]
• Continuous Meta-Learning without TasksJames Harrison, Apoorva Sharma, Chelsea Finn, Marco Pavone. [doi]
• Axioms for Learning from Pairwise ComparisonsRitesh Noothigattu, Dominik Peters, Ariel D. Procaccia. [doi]
• Constant-Expansion Suffices for Compressed Sensing with Generative PriorsConstantinos Daskalakis, Dhruv Rohatgi, Emmanouil Zampetakis. [doi]
• Leap-Of-Thought: Teaching Pre-Trained Models to Systematically Reason Over Implicit KnowledgeAlon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, Jonathan Berant. [doi]
• On the Role of Sparsity and DAG Constraints for Learning Linear DAGsIgnavier Ng, AmirEmad Ghassami, Kun Zhang 0001. [doi]
• Post-training Iterative Hierarchical Data Augmentation for Deep NetworksAdil Khan 0001, Khadija Fraz. [doi]
• MDP Homomorphic Networks: Group Symmetries in Reinforcement LearningElise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling. [doi]
• A Loss Function for Generative Neural Networks Based on Watson's Perceptual ModelSteffen Czolbe, Oswin Krause, Ingemar J. Cox, Christian Igel. [doi]
• Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret AlgorithmLin Yang, Mohammad Hassan Hajiesmaili, Mohammad Sadegh Talebi, John C. S. Lui, Wing Shing Wong. [doi]
• Confounding-Robust Policy Evaluation in Infinite-Horizon Reinforcement LearningNathan Kallus, Angela Zhou. [doi]
• Deep active inference agents using Monte-Carlo methodsZafeirios Fountas, Noor Sajid, Pedro A. M. Mediano, Karl J. Friston. [doi]
• IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian MethodYossi Arjevani, Joan Bruna, Bugra Can, Mert Gürbüzbalaban, Stefanie Jegelka, Hongzhou Lin. [doi]
• Multiview Neural Surface Reconstruction by Disentangling Geometry and AppearanceLior Yariv, Yoni Kasten, Dror Moran, Meirav Galun, Matan Atzmon, Ronen Basri, Yaron Lipman. [doi]
• Learning to Utilize Shaping Rewards: A New Approach of Reward ShapingYujing Hu, Weixun Wang, Hangtian Jia, Yixiang Wang, Yingfeng Chen, Jianye Hao, Feng Wu 0001, Changjie Fan. [doi]
• HYDRA: Pruning Adversarially Robust Neural NetworksVikash Sehwag, Shiqi Wang 0002, Prateek Mittal, Suman Jana. [doi]
• Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic SegmentationGuoliang Kang, Yunchao Wei, Yi Yang 0001, Yueting Zhuang, Alexander G. Hauptmann. [doi]
• Modeling Continuous Stochastic Processes with Dynamic Normalizing FlowsRuizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann. [doi]
• A Scalable MIP-based Method for Learning Optimal Multivariate Decision TreesHaoran Zhu, Pavankumar Murali, Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam. [doi]
• Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric UncertaintyMiguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker. [doi]
• Policy Improvement via Imitation of Multiple OraclesChing-An Cheng, Andrey Kolobov, Alekh Agarwal. [doi]
• Sparse Weight Activation TrainingMd Aamir Raihan, Tor M. Aamodt. [doi]
• RL Unplugged: A Collection of Benchmarks for Offline Reinforcement LearningÇaglar Gülçehre, Ziyu Wang 0001, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi 0002, Matthew Hoffman 0002, Nicolas Heess, Nando de Freitas. [doi]
• The Value Equivalence Principle for Model-Based Reinforcement LearningChristopher Grimm, André Barreto, Satinder Singh, David Silver. [doi]
• Learning Affordance Landscapes for Interaction Exploration in 3D EnvironmentsTushar Nagarajan, Kristen Grauman. [doi]
• Intra-Processing Methods for Debiasing Neural NetworksYash Savani, Colin White, Naveen Sundar Govindarajulu. [doi]
• Beta R-CNN: Looking into Pedestrian Detection from Another PerspectiveZixuan Xu, Banghuai Li, Ye Yuan, Anhong Dang. [doi]
• Smoothed Geometry for Robust AttributionZifan Wang, Haofan Wang, Shakul Ramkumar, Piotr Mardziel, Matt Fredrikson, Anupam Datta. [doi]
• Optimization and Generalization of Shallow Neural Networks with Quadratic Activation FunctionsStefano Sarao Mannelli, Eric Vanden-Eijnden, Lenka Zdeborová. [doi]
• Universal guarantees for decision tree induction via a higher-order splitting criterionGuy Blanc, Neha Gupta 0002, Jane Lange, Li-Yang Tan. [doi]
• Deep Subspace Clustering with Data AugmentationMahdi Abavisani, Alireza Naghizadeh, Dimitris N. Metaxas, Vishal M. Patel. [doi]
• One-sample Guided Object Representation DisassemblingZunlei Feng, Yongming He, Xinchao Wang, Xin Gao, Jie Lei, Cheng Jin, Mingli Song. [doi]
• One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RLSaurabh Kumar, Aviral Kumar, Sergey Levine, Chelsea Finn. [doi]
• Incorporating Pragmatic Reasoning Communication into Emergent LanguageYipeng Kang, Tonghan Wang 0001, Gerard de Melo. [doi]
• Safe Reinforcement Learning via Curriculum InductionMatteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause 0001, Alekh Agarwal. [doi]
• Online Bayesian PersuasionMatteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti 0001. [doi]
• A Scalable Approach for Privacy-Preserving Collaborative Machine LearningJinhyun So, Basak Güler, Salman Avestimehr. [doi]
• Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution ExamplesJay Nandy, Wynne Hsu, Mong-Li Lee. [doi]
• Robust Quantization: One Model to Rule Them AllMoran Shkolnik, Brian Chmiel, Ron Banner, Gil Shomron, Yury Nahshan, Alex M. Bronstein, Uri C. Weiser. [doi]
• Continuous Object Representation Networks: Novel View Synthesis without Target View SupervisionNicolai Häni, Selim Engin, Jun-Jee Chao, Volkan Isler. [doi]
• Detecting Hands and Recognizing Physical Contact in the WildSupreeth Narasimhaswamy, Trung Nguyen, Minh Hoai Nguyen. [doi]
• Discovering Symbolic Models from Deep Learning with Inductive BiasesMiles D. Cranmer, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Rui Xu, Kyle Cranmer, David N. Spergel, Shirley Ho. [doi]
• Adversarial Learning for Robust Deep ClusteringXu Yang 0019, Cheng Deng, Kun Wei, Junchi Yan, Wei Liu. [doi]
• Stochastic Normalizing FlowsHao Wu 0035, Jonas Köhler, Frank Noé. [doi]
• Sharp uniform convergence bounds through empirical centralizationCyrus Cousins, Matteo Riondato. [doi]
• Sharp Representation Theorems for ReLU Networks with Precise Dependence on DepthGuy Bresler, Dheeraj Nagaraj. [doi]
• Sampling from a k-DPP without looking at all itemsDaniele Calandriello, Michal Derezinski, Michal Valko. [doi]
• No-Regret Learning Dynamics for Extensive-Form Correlated EquilibriumAndrea Celli, Alberto Marchesi, Gabriele Farina, Nicola Gatti 0001. [doi]
• ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICAIlyes Khemakhem, Ricardo Pio Monti, Diederik P. Kingma, Aapo Hyvärinen. [doi]
• Fewer is More: A Deep Graph Metric Learning Perspective Using Fewer ProxiesYuehua Zhu, Muli Yang, Cheng Deng, Wei Liu 0005. [doi]
• Greedy inference with structure-exploiting lazy mapsMichael Brennan, Daniele Bigoni, Olivier Zahm, Alessio Spantini, Youssef Marzouk. [doi]
• Debiased Contrastive LearningChing-Yao Chuang, Joshua Robinson, Yen-Chen Lin, Antonio Torralba 0001, Stefanie Jegelka. [doi]
• Reinforcement Learning with Feedback GraphsChristoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan. [doi]
• Deep Energy-based Modeling of Discrete-Time PhysicsTakashi Matsubara, Ai Ishikawa, Takaharu Yaguchi. [doi]
• On the Equivalence between Online and Private Learnability beyond Binary ClassificationYoung-Hun Jung, Baekjin Kim, Ambuj Tewari. [doi]
• TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language TranslationDongxu Li, Chenchen Xu, Xin Yu 0002, Kaihao Zhang, Benjamin Swift, Hanna Suominen, Hongdong Li. [doi]
• Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe MethodKiran Koshy Thekumparampil, Prateek Jain 0002, Praneeth Netrapalli, Sewoong Oh. [doi]
• Gradient Boosted Normalizing FlowsRobert A. Giaquinto, Arindam Banerjee. [doi]
• Improving Natural Language Processing Tasks with Human Gaze-Guided Neural AttentionEkta Sood, Simon Tannert, Philipp Mueller, Andreas Bulling. [doi]
• Displacement-Invariant Matching Cost Learning for Accurate Optical Flow EstimationJianyuan Wang, Yiran Zhong, Yuchao Dai, Kaihao Zhang, Pan Ji, Hongdong Li. [doi]
• Watch out! Motion is Blurring the Vision of Your Deep Neural NetworksQing Guo 0005, Felix Juefei-Xu, Xiaofei Xie, Lei Ma 0003, Jian Wang, Bing Yu, Wei Feng 0005, Yang Liu 0003. [doi]
• Bayesian PseudocoresetsDionysis Manousakas, Zuheng Xu, Cecilia Mascolo, Trevor Campbell. [doi]
• Contrastive learning of global and local features for medical image segmentation with limited annotationsKrishna Chaitanya, Ertunc Erdil, Neerav Karani, Ender Konukoglu. [doi]
• SURF: A Simple, Universal, Robust, Fast Distribution Learning AlgorithmYi Hao, Ayush Jain, Alon Orlitsky, Vaishakh Ravindrakumar. [doi]
• Dirichlet Graph Variational AutoencoderJia Li, Jianwei Yu, Jiajin Li, Honglei Zhang, Kangfei Zhao, Yu Rong, Hong Cheng 0001, JunZhou Huang. [doi]
• Multilabel Classification by Hierarchical Partitioning and Data-dependent GroupingShashanka Ubaru, Sanjeeb Dash, Arya Mazumdar, Oktay Günlük. [doi]
• Adaptive Reduced Rank RegressionQiong Wu 0008, Felix Ming Fai Wong, Yanhua Li, Zhenming Liu, Varun Kanade. [doi]
• Adaptive Experimental Design with Temporal Interference: A Maximum Likelihood ApproachPeter W. Glynn, Ramesh Johari, Mohammad Rasouli 0001. [doi]
• Active Invariant Causal Prediction: Experiment Selection through StabilityJuan Gamella, Christina Heinze-Deml. [doi]
• Targeted Adversarial Perturbations for Monocular Depth PredictionAlex Wong, Safa Cicek, Stefano Soatto. [doi]
• O(n) Connections are Expressive Enough: Universal Approximability of Sparse TransformersChulhee Yun, Yin-Wen Chang, Srinadh Bhojanapalli, Ankit Singh Rawat, Sashank J. Reddi, Sanjiv Kumar. [doi]
• HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech SynthesisJungil Kong, Jaehyeon Kim, Jaekyoung Bae. [doi]
• Normalizing Kalman Filters for Multivariate Time Series AnalysisEmmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski. [doi]
• Residual Distillation: Towards Portable Deep Neural Networks without ShortcutsGuilin Li, Junlei Zhang, Yunhe Wang, Chuanjian Liu, Matthias Tan, Yunfeng Lin, Wei Zhang, Jiashi Feng, Tong Zhang. [doi]
• Planning in Markov Decision Processes with Gap-Dependent Sample ComplexityAnders Jonsson, Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Edouard Leurent, Michal Valko. [doi]
• Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstructionDavid Novotný, Roman Shapovalov, Andrea Vedaldi. [doi]
• SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite MeteorologyMark S. Veillette, Siddharth Samsi, Christopher J. Mattioli. [doi]
• Why are Adaptive Methods Good for Attention Models?Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra. [doi]
• Adversarial Blocking BanditsNick Bishop, Hau Chan, Debmalya Mandal, Long Tran-Thanh. [doi]
• The Lottery Ticket Hypothesis for Pre-trained BERT NetworksTianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu 0001, Yang Zhang, Zhangyang Wang, Michael Carbin. [doi]
• Natural Graph NetworksPim de Haan, Taco S. Cohen, Max Welling. [doi]
• BERT Loses Patience: Fast and Robust Inference with Early ExitWangchunshu Zhou, Canwen Xu, Tao Ge, Julian J. McAuley, Ke Xu 0001, Furu Wei. [doi]
• Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial AttacksWei-An Lin, Chun Pong Lau 0001, Alexander Levine 0001, Rama Chellappa, Soheil Feizi. [doi]
• Adversarial Example GamesAvishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton. [doi]
• Pruning neural networks without any data by iteratively conserving synaptic flowHidenori Tanaka, Daniel Kunin, Daniel L. Yamins, Surya Ganguli. [doi]
• Adversarial Weight Perturbation Helps Robust GeneralizationDongxian Wu, Shu-Tao Xia, Yisen Wang 0001. [doi]
• Joints in Random ForestsAlvaro H. C. Correia, Robert Peharz, Cassio P. de Campos. [doi]
• Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample ComplexityHaim Kaplan, Yishay Mansour, Uri Stemmer, Eliad Tsfadia. [doi]
• Further Analysis of Outlier Detection with Deep Generative ModelsZiyu Wang 0006, Bin Dai, David P. Wipf, Jun Zhu. [doi]
• Variational Amodal Object CompletionHuan Ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler. [doi]
• Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian InferenceDisi Ji, Padhraic Smyth, Mark Steyvers. [doi]
• The Generalization-Stability Tradeoff In Neural Network PruningBrian Bartoldson, Ari S. Morcos, Adrian Barbu, Gordon Erlebacher. [doi]
• Robust Meta-learning for Mixed Linear Regression with Small BatchesWeihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh. [doi]
• Measuring Robustness to Natural Distribution Shifts in Image ClassificationRohan Taori, Achal Dave, Vaishaal Shankar, Nicholas Carlini, Benjamin Recht, Ludwig Schmidt. [doi]
• Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon PredictionMichael Janner, Igor Mordatch, Sergey Levine. [doi]
• A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descentZhenyu Liao, Romain Couillet, Michael W. Mahoney. [doi]
• Certifying Strategyproof Auction NetworksMichael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson 0001. [doi]
• Robustness of Community Detection to Random Geometric PerturbationsSandrine Péché, Vianney Perchet. [doi]
• CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative ModelsVijil Chenthamarakshan, Payel Das, Samuel C. Hoffman, Hendrik Strobelt, Inkit Padhi, Kar Wai Lim, Benjamin Hoover, Matteo Manica, Jannis Born, Teodoro Laino, Aleksandra Mojsilovic. [doi]
• Online Meta-Critic Learning for Off-Policy Actor-Critic MethodsWei Zhou, Yiying Li, Yongxin Yang, Huaimin Wang, Timothy M. Hospedales. [doi]
• Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field TheoryYufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang. [doi]
• Non-Stochastic Control with Bandit FeedbackPaula Gradu, John Hallman, Elad Hazan. [doi]
• Towards Minimax Optimal Reinforcement Learning in Factored Markov Decision ProcessesYi Tian, Jian Qian, Suvrit Sra. [doi]
• Causal Imitation Learning With Unobserved ConfoundersJunzhe Zhang, Daniel Kumor, Elias Bareinboim. [doi]
• Regularized linear autoencoders recover the principal components, eventuallyXuchan Bao, James Lucas, Sushant Sachdeva, Roger B. Grosse. [doi]
• Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without ForgettingJorge A. Mendez, Boyu Wang, Eric Eaton. [doi]
• Improving Online Rent-or-Buy Algorithms with Sequential Decision Making and ML PredictionsSoumya Banerjee. [doi]
• Neural Methods for Point-wise Dependency EstimationYao-Hung Hubert Tsai, Han Zhao 0002, Makoto Yamada, Louis-Philippe Morency, Russ R. Salakhutdinov. [doi]
• Fairness constraints can help exact inference in structured predictionKevin Bello, Jean Honorio. [doi]
• One-bit Supervision for Image ClassificationHengtong Hu, Lingxi Xie, Zewei Du, Richang Hong, Qi Tian 0001. [doi]
• Provably Robust Metric LearningLu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang 0001, Cho-Jui Hsieh. [doi]
• Learning Bounds for Risk-sensitive LearningJaeho Lee, Sejun Park, Jinwoo Shin. [doi]
• Robust Persistence Diagrams using Reproducing KernelsSiddharth Vishwanath, Kenji Fukumizu, Satoshi Kuriki, Bharath K. Sriperumbudur. [doi]
• An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear BanditsJulian Katz-Samuels, Lalit Jain, Zohar Karnin, Kevin G. Jamieson. [doi]
• A Bandit Learning Algorithm and Applications to Auction DesignKim Thang Nguyen. [doi]
• Stochastic NormalizationZhi Kou, Kaichao You, Mingsheng Long, Jianmin Wang 0001. [doi]
• Forethought and Hindsight in Credit AssignmentVeronica Chelu, Doina Precup, Hado van Hasselt. [doi]
• UWSOD: Toward Fully-Supervised-Level Capacity Weakly Supervised Object DetectionYunhang Shen, Rongrong Ji, Zhiwei Chen, Yongjian Wu, Feiyue Huang. [doi]
• Color Visual Illusions: A Statistics-based Computational ModelElad Hirsch, Ayellet Tal. [doi]
• Cycle-Contrast for Self-Supervised Video Representation LearningQuan Kong, Wenpeng Wei, Ziwei Deng, Tomoaki Yoshinaga, Tomokazu Murakami. [doi]
• Munchausen Reinforcement LearningNino Vieillard, Olivier Pietquin, Matthieu Geist. [doi]
• Optimal Adaptive Electrode Selection to Maximize Simultaneously Recorded Neuron YieldJohn S. Choi, Krishan Kumar, Mohammad Khazali, Katie Wingel, Mahdi Choudhury, Adam S. Charles, Bijan Pesaran. [doi]
• Multiscale Deep Equilibrium ModelsShaojie Bai, Vladlen Koltun, J. Zico Kolter. [doi]
• Latent Dynamic Factor Analysis of High-Dimensional Neural RecordingsHeejong Bong, Zongge Liu, Zhao Ren, Matthew A. Smith, Valérie Ventura, Robert E. Kass. [doi]
• Minimax Value Interval for Off-Policy Evaluation and Policy OptimizationNan Jiang, Jiawei Huang. [doi]
• Provably Good Batch Off-Policy Reinforcement Learning Without Great ExplorationYao Liu 0009, Adith Swaminathan, Alekh Agarwal, Emma Brunskill. [doi]
• Robust Reinforcement Learning via Adversarial training with Langevin DynamicsParameswaran Kamalaruban, Yu-Ting Huang, Ya-Ping Hsieh, Paul Rolland, Cheng Shi, Volkan Cevher. [doi]
• Few-shot Visual Reasoning with Meta-Analogical Contrastive LearningYoungsung Kim, Jinwoo Shin, Eunho Yang, Sung Ju Hwang. [doi]
• Learning of Discrete Graphical Models with Neural NetworksAbhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra, Marc Vuffray. [doi]
• A Unified Switching System Perspective and Convergence Analysis of Q-Learning AlgorithmsDonghwan Lee 0002, Niao He. [doi]
• Efficient Learning of Discrete Graphical ModelsMarc Vuffray, Sidhant Misra, Andrey Y. Lokhov. [doi]
• Counterexample-Guided Learning of Monotonic Neural NetworksAishwarya Sivaraman, Golnoosh Farnadi, Todd D. Millstein, Guy Van den Broeck. [doi]
• Gaussian Process Bandit Optimization of the Thermodynamic Variational ObjectiveVu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood. [doi]
• Training Stronger Baselines for Learning to OptimizeTianlong Chen, Weiyi Zhang, Jingyang Zhou, Shiyu Chang, Sijia Liu 0001, Lisa Amini, Zhangyang Wang. [doi]
• A Game Theoretic Analysis of Additive Adversarial Attacks and DefensesAmbar Pal, René Vidal. [doi]
• A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous SamplingXiaotie Deng, Ron Lavi, Tao Lin, Qi Qi 0003, Wenwei Wang, Xiang Yan. [doi]
• EcoLight: Intersection Control in Developing Regions Under Extreme Budget and Network ConstraintsSachin Chauhan, Kashish Bansal, Rijurekha Sen. [doi]
• Manifold GPLVMs for discovering non-Euclidean latent structure in neural dataKristopher T. Jensen, Ta-Chu Kao, Marco Tripodi, Guillaume Hennequin. [doi]
• Beyond Lazy Training for Over-parameterized Tensor DecompositionXiang Wang, Chenwei Wu 0002, Jason D. Lee, Tengyu Ma, Rong Ge 0001. [doi]
• Certifying Confidence via Randomized SmoothingAounon Kumar, Alexander Levine 0001, Soheil Feizi, Tom Goldstein. [doi]
• Private Identity Testing for High-Dimensional DistributionsClément L. Canonne, Gautam Kamath 0001, Audra McMillan, Jonathan R. Ullman, Lydia Zakynthinou. [doi]
• Barking up the right tree: an approach to search over molecule synthesis DAGsJohn Bradshaw, Brooks Paige, Matt J. Kusner, Marwin H. S. Segler, José Miguel Hernández-Lobato. [doi]
• Distributed Newton Can Communicate Less and Resist Byzantine WorkersAvishek Ghosh, Raj Kumar Maity, Arya Mazumdar. [doi]
• Convolutional Generation of Textured 3D MeshesDario Pavllo, Graham Spinks, Thomas Hofmann, Marie-Francine Moens, Aurélien Lucchi. [doi]
• A Closer Look at Accuracy vs. RobustnessYao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Russ R. Salakhutdinov, Kamalika Chaudhuri. [doi]
• Optimal Approximation - Smoothness Tradeoffs for Soft-Max FunctionsAlessandro Epasto, Mohammad Mahdian, Vahab S. Mirrokni, Emmanouil Zampetakis. [doi]
• The Smoothed Possibility of Social ChoiceLirong Xia. [doi]
• Learning Structured Distributions From Untrusted Batches: Faster and SimplerSitan Chen, Jerry Li 0001, Ankur Moitra. [doi]
• Invertible Gaussian Reparameterization: Revisiting the Gumbel-SoftmaxAndres Potapczynski, Gabriel Loaiza-Ganem, John P. Cunningham. [doi]
• FedSplit: an algorithmic framework for fast federated optimizationReese Pathak, Martin J. Wainwright. [doi]
• Discovering Reinforcement Learning AlgorithmsJunhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver. [doi]
• Few-Cost Salient Object Detection with Adversarial-Paced LearningDingwen Zhang, Haibin Tian, Jungong Han. [doi]
• On Reward-Free Reinforcement Learning with Linear Function ApproximationRuosong Wang, Simon S. Du, Lin F. Yang, Russ R. Salakhutdinov. [doi]
• Learning Strategic Network Emergence GamesRakshit Trivedi, Hongyuan Zha. [doi]
• CoADNet: Collaborative Aggregation-and-Distribution Networks for Co-Salient Object DetectionQijian Zhang, Runmin Cong, Junhui Hou, Chongyi Li, Yao Zhao. [doi]
• Recurrent Quantum Neural NetworksJohannes Bausch. [doi]
• Bayesian Deep Learning and a Probabilistic Perspective of GeneralizationAndrew Gordon Wilson, Pavel Izmailov. [doi]
• MomentumRNN: Integrating Momentum into Recurrent Neural NetworksTan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang. [doi]
• How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?Mrinank Sharma, Sören Mindermann, Jan Markus Brauner, Gavin Leech, Anna B. Stephenson, Tomas Gavenciak, Jan Kulveit, Yee Whye Teh, Leonid Chindelevitch, Yarin Gal. [doi]
• Regret in Online Recommendation SystemsKaito Ariu, Narae Ryu, Se-Young Yun, Alexandre Proutière. [doi]
• Learning discrete distributions with infinite supportDoron Cohen, Aryeh Kontorovich, Geoffrey Wolfer. [doi]
• CASTLE: Regularization via Auxiliary Causal Graph DiscoveryTrent Kyono, Yao Zhang, Mihaela van der Schaar. [doi]
• Grasp Proposal Networks: An End-to-End Solution for Visual Learning of Robotic GraspsChaozheng Wu, Jian Chen, Qiaoyu Cao, Jianchi Zhang, Yunxin Tai, Lin Sun 0004, Kui Jia. [doi]
• Rational neural networksNicolas Boullé, Yuji Nakatsukasa, Alex Townsend. [doi]
• What Makes for Good Views for Contrastive Learning?Yonglong Tian, Chen Sun 0002, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola. [doi]
• Shared Experience Actor-Critic for Multi-Agent Reinforcement LearningFilippos Christianos, Lukas Schäfer, Stefano V. Albrecht. [doi]
• Off-Policy Evaluation via the Regularized LagrangianMengjiao Yang, Ofir Nachum, Bo Dai, Lihong Li 0001, Dale Schuurmans. [doi]
• Curvature Regularization to Prevent Distortion in Graph EmbeddingHongbin Pei, Bingzhe Wei, Kevin Chang 0001, Chunxu Zhang, Bo Yang. [doi]
• Deep Reinforcement and InfoMax LearningBogdan Mazoure, Remi Tachet des Combes, Thang Doan, Philip Bachman, R. Devon Hjelm. [doi]
• Conformal Symplectic and Relativistic OptimizationGuilherme França, Jeremias Sulam, Daniel P. Robinson, René Vidal. [doi]
• Convolutional Tensor-Train LSTM for Spatio-Temporal LearningJiahao Su, Wonmin Byeon, Jean Kossaifi, Furong Huang, Jan Kautz, Anima Anandkumar. [doi]
• Primal-Dual Mesh Convolutional Neural NetworksFrancesco Milano, Antonio Loquercio, Antoni Rosinol, Davide Scaramuzza 0001, Luca Carlone. [doi]
• Provably Efficient Online Hyperparameter Optimization with Population-Based BanditsJack Parker-Holder, Vu Nguyen, Stephen J. Roberts. [doi]
• How Can I Explain This to You? An Empirical Study of Deep Neural Network Explanation MethodsJeya Vikranth Jeyakumar, Joseph Noor, Yu-Hsi Cheng, Luis Garcia, Mani B. Srivastava. [doi]
• Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge GraphsHongyu Ren, Jure Leskovec. [doi]
• Timeseries Anomaly Detection using Temporal Hierarchical One-Class NetworkLifeng Shen, Zhuocong Li, James Kwok. [doi]
• Biologically Inspired Mechanisms for Adversarial RobustnessManish V. Reddy, Andrzej Banburski, Nishka Pant, Tomaso A. Poggio. [doi]
• Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddingsChristopher Morris 0001, Gaurav Rattan, Petra Mutzel. [doi]
• Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior ApproximationsSebastian Farquhar, Lewis Smith, Yarin Gal. [doi]
• Independent Policy Gradient Methods for Competitive Reinforcement LearningConstantinos Daskalakis, Dylan J. Foster, Noah Golowich. [doi]
• Reward-rational (implicit) choice: A unifying formalism for reward learningHong Jun Jeon, Smitha Milli, Anca D. Dragan. [doi]
• Reparameterizing Mirror Descent as Gradient DescentEhsan Amid, Manfred K. Warmuth. [doi]
• Benchmarking Deep Inverse Models over time, and the Neural-Adjoint methodSimiao Ren, Willie Padilla, Jordan M. Malof. [doi]
• Learning to Orient Surfaces by Self-supervised Spherical CNNsRiccardo Spezialetti, Federico Stella, Marlon Marcon, Luciano Silva, Samuele Salti, Luigi di Stefano. [doi]
• Inverse Reinforcement Learning from a Gradient-based LearnerGiorgia Ramponi, Gianluca Drappo, Marcello Restelli. [doi]
• Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian OptimizationGeoff Pleiss, Martin Jankowiak, David Eriksson, Anil Damle, Jacob R. Gardner. [doi]
• Compositional Generalization by Learning Analytical ExpressionsQian Liu, Shengnan An, Jian-Guang Lou, Bei Chen, Zeqi Lin, Yan Gao 0002, Bin Zhou, Nanning Zheng 0001, Dongmei Zhang. [doi]
• Gibbs Sampling with PeoplePeter M. C. Harrison, Raja Marjieh, Federico Adolfi, Pol van Rijn, Manuel Anglada-Tort, Ofer Tchernichovski, Pauline Larrouy-Maestri, Nori Jacoby. [doi]
• Self-supervised learning through the eyes of a childA. Emin Orhan, Vaibhav V. Gupta, Brenden M. Lake. [doi]
• Continuous Regularized Wasserstein BarycentersLingxiao Li, Aude Genevay, Mikhail Yurochkin, Justin M. Solomon. [doi]
• BayReL: Bayesian Relational Learning for Multi-omics Data IntegrationEhsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan 0001, Xiaoning Qian. [doi]
• Swapping Autoencoder for Deep Image ManipulationTaesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang 0001. [doi]
• Posterior Re-calibration for Imbalanced DatasetsJunjiao Tian, Yen-Cheng Liu, Nathaniel Glaser, Yen-Chang Hsu, Zsolt Kira. [doi]
• Critic Regularized RegressionZiyu Wang 0001, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas. [doi]
• Efficient Learning of Generative Models via Finite-Difference Score MatchingTianyu Pang, Taufik Xu, Chongxuan Li, Yang Song 0011, Stefano Ermon, Jun Zhu 0001. [doi]
• Hierarchical Gaussian Process Priors for Bayesian Neural Network WeightsTheofanis Karaletsos, Thang D. Bui. [doi]
• Towards Deeper Graph Neural Networks with Differentiable Group NormalizationKaixiong Zhou, Xiao Huang 0001, Yuening Li, Daochen Zha, Rui Chen, Xia Hu. [doi]
• DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of EnsemblesHuanrui Yang, Jingyang Zhang, Hongliang Dong, Nathan Inkawhich, Andrew Gardner, Andrew Touchet, Wesley Wilkes, Heath Berry, Hai Li 0001. [doi]
• HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet LossYurun Tian, Axel Barroso Laguna, Tony Ng, Vassileios Balntas, Krystian Mikolajczyk. [doi]
• Hybrid Models for Learning to BranchPrateek Gupta, Maxime Gasse, Elias B. Khalil, Pawan Kumar Mudigonda, Andrea Lodi 0001, Yoshua Bengio. [doi]
• Multipole Graph Neural Operator for Parametric Partial Differential EquationsZongyi Li, Nikola B. Kovachki, Kamyar Azizzadenesheli, Burigede Liu, Andrew M. Stuart, Kaushik Bhattacharya, Anima Anandkumar. [doi]
• Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite MatricesJohn C. Duchi, Oliver Hinder, Andrew Naber, Yinyu Ye. [doi]
• Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network EmbeddingLin Lan, Pinghui Wang, Xuefeng Du, Kaikai Song, Jing Tao, Xiaohong Guan. [doi]
• Attribution Preservation in Network Compression for Reliable Network InterpretationGeondo Park, June Yong Yang, Sung Ju Hwang, Eunho Yang. [doi]
• Neurosymbolic Reinforcement Learning with Formally Verified ExplorationGreg Anderson, Abhinav Verma, Isil Dillig, Swarat Chaudhuri. [doi]
• Time-Reversal Symmetric ODE NetworkIn Huh, Eunho Yang, Sung Ju Hwang, Jinwoo Shin. [doi]
• An Efficient Framework for Clustered Federated LearningAvishek Ghosh, Jichan Chung, Dong Yin, Kannan Ramchandran. [doi]
• Semialgebraic Optimization for Lipschitz Constants of ReLU NetworksTong Chen 0002, Jean B. Lasserre, Victor Magron, Edouard Pauwels. [doi]
• Kalman Filtering Attention for User Behavior Modeling in CTR PredictionHu Liu, Jing Lu, Xiwei Zhao, Sulong Xu, Hao Peng, Yutong Liu, Zehua Zhang, Jian Li, Junsheng Jin, Yongjun Bao, Weipeng Yan. [doi]
• Recursive Inference for Variational AutoencodersMinyoung Kim, Vladimir Pavlovic. [doi]
• Uncertainty-aware Self-training for Few-shot Text ClassificationSubhabrata Mukherjee, Ahmed Hassan Awadallah. [doi]
• Open Graph Benchmark: Datasets for Machine Learning on GraphsWeihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec. [doi]
• Learning under Model Misspecification: Applications to Variational and Ensemble methodsAndrés R. Masegosa. [doi]
• Classification with Valid and Adaptive CoverageYaniv Romano, Matteo Sesia, Emmanuel J. Candès. [doi]
• Training Generative Adversarial Networks with Limited DataTero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila. [doi]
• An Analysis of SVD for Deep Rotation EstimationJake Levinson, Carlos Esteves, Kefan Chen, Noah Snavely, Angjoo Kanazawa, Afshin Rostamizadeh, Ameesh Makadia. [doi]
• MeshSDF: Differentiable Iso-Surface ExtractionEdoardo Remelli, Artem Lukoianov, Stephan R. Richter, Benoît Guillard, Timur M. Bagautdinov, Pierre Baqué, Pascal Fua. [doi]
• Joint Policy Search for Multi-agent Collaboration with Imperfect InformationYuandong Tian, Qucheng Gong, Yu Jiang. [doi]
• Universal Domain Adaptation through Self SupervisionKuniaki Saito, Donghyun Kim, Stan Sclaroff, Kate Saenko. [doi]
• Fair Multiple Decision Making Through Soft InterventionsYaowei Hu, Yongkai Wu, Lu Zhang 0021, Xintao Wu. [doi]
• Faithful Embeddings for Knowledge Base QueriesHaitian Sun, Andrew O. Arnold, Tania Bedrax-Weiss, Fernando Pereira 0003, William W. Cohen. [doi]
• The Convolution Exponential and Generalized Sylvester FlowsEmiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling. [doi]
• De-Anonymizing Text by Fingerprinting Language GenerationZhen Sun, Roei Schuster, Vitaly Shmatikov. [doi]
• UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field MessagingChaoning Zhang, Philipp Benz, Adil Karjauv, Geng Sun, In-So Kweon. [doi]
• Language-Conditioned Imitation Learning for Robot Manipulation TasksSimon Stepputtis, Joseph Campbell, Mariano J. Phielipp, Stefan Lee, Chitta Baral, Heni Ben Amor. [doi]
• Train-by-Reconnect: Decoupling Locations of Weights from Their ValuesYushi Qiu, Reiji Suda. [doi]
• Understanding Approximate Fisher Information for Fast Convergence of Natural Gradient Descent in Wide Neural NetworksRyo Karakida, Kazuki Osawa. [doi]
• Community detection in sparse time-evolving graphs with a dynamical Bethe-HessianLorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay. [doi]
• Sample Efficient Reinforcement Learning via Low-Rank Matrix EstimationDevavrat Shah, Dogyoon Song, Zhi Xu, Yuzhe Yang. [doi]
• Using noise to probe recurrent neural network structure and prune synapsesEli Moore, Rishidev Chaudhuri. [doi]
• STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural NetworksMeiyi Ma, Ji Gao, Lu Feng 0001, John A. Stankovic. [doi]
• Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the HessianJack Parker-Holder, Luke Metz, Cinjon Resnick, Hengyuan Hu, Adam Lerer, Alistair Letcher, Alexander Peysakhovich, Aldo Pacchiano, Jakob N. Foerster. [doi]
• Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled RegularizationMichal Derezinski, Burak Bartan, Mert Pilanci, Michael W. Mahoney. [doi]
• Interior Point Solving for LP-based prediction+optimisationJayanta Mandi, Tias Guns. [doi]
• PLANS: Neuro-Symbolic Program Learning from VideosRaphaël Dang-Nhu. [doi]
• Cross-validation Confidence Intervals for Test ErrorPierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey. [doi]
• See, Hear, Explore: Curiosity via Audio-Visual AssociationVictoria Dean, Shubham Tulsiani, Abhinav Gupta 0001. [doi]
• Linear Time Sinkhorn Divergences using Positive FeaturesMeyer Scetbon, Marco Cuturi. [doi]
• High-Fidelity Generative Image CompressionFabian Mentzer, George Toderici, Michael Tschannen, Eirikur Agustsson. [doi]
• Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous ControlZhiyuan Xu, Kun Wu, Zhengping Che, Jian Tang 0008, Jieping Ye. [doi]
• Dissecting Neural ODEsStefano Massaroli, Michael Poli, Jinkyoo Park, Atsushi Yamashita, Hajime Asama. [doi]
• Graph Cross Networks with Vertex Infomax PoolingMaosen Li, Siheng Chen, Ya Zhang 0002, Ivor W. Tsang. [doi]
• Can Graph Neural Networks Count Substructures?Zhengdao Chen, Lei Chen 0062, Soledad Villar, Joan Bruna. [doi]
• Soft Contrastive Learning for Visual LocalizationJanine Thoma, Danda Pani Paudel, Luc Van Gool. [doi]
• Ultrahyperbolic Representation LearningMarc T. Law, Jos Stam. [doi]
• Measuring Systematic Generalization in Neural Proof Generation with TransformersNicolas Gontier, Koustuv Sinha, Siva Reddy, Christopher Pal. [doi]
• On Second Order Behaviour in Augmented Neural ODEsAlexander Norcliffe, Cristian Bodnar, Ben Day, Nikola Simidjievski, Pietro Lió. [doi]
• Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary SeminormsSascha Saralajew, Lars Holdijk, Thomas Villmann. [doi]
• Optimal Variance Control of the Score-Function Gradient Estimator for Importance-Weighted BoundsValentin Liévin, Andrea Dittadi, Anders Christensen, Ole Winther. [doi]
• Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?Shen Yan, Yu Zheng, Wei Ao, Xiao Zeng, Mi Zhang 0002. [doi]
• Learning to Learn with Feedback and Local PlasticityJack Lindsey, Ashok Litwin-Kumar. [doi]
• Learning from Mixtures of Private and Public PopulationsRaef Bassily, Shay Moran, Anupama Nandi. [doi]
• Improved Variational Bayesian Phylogenetic Inference with Normalizing FlowsCheng Zhang. [doi]
• Consistency Regularization for Certified Robustness of Smoothed ClassifiersJongheon Jeong, Jinwoo Shin. [doi]
• Joint Contrastive Learning with Infinite PossibilitiesQi Cai, Yu Wang, Yingwei Pan, Ting Yao, Tao Mei 0001. [doi]
• Relative gradient optimization of the Jacobian term in unsupervised deep learningLuigi Gresele, Giancarlo Fissore, Adrián Javaloy, Bernhard Schölkopf, Aapo Hyvärinen. [doi]
• VarGrad: A Low-Variance Gradient Estimator for Variational InferenceLorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz. [doi]
• Synthetic Data Generators - Sequential and PrivateOlivier Bousquet, Roi Livni, Shay Moran. [doi]
• Calibrated Reliable Regression using Maximum Mean DiscrepancyPeng Cui, Wenbo Hu 0001, Jun Zhu 0001. [doi]
• Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect TeacherGuangda Ji, Zhanxing Zhu. [doi]
• p-Sampling Without ReplacementEdith Cohen, Rasmus Pagh, David P. Woodruff. [doi]
• AdaShare: Learning What To Share For Efficient Deep Multi-Task LearningXimeng Sun, Rameswar Panda, Rogério Feris, Kate Saenko. [doi]
• Finding the Homology of Decision Boundaries with Active LearningWeizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha. [doi]
• Deep Inverse Q-learning with ConstraintsGabriel Kalweit, Maria Hügle, Moritz Werling, Joschka Boedecker. [doi]
• On Warm-Starting Neural Network TrainingJordan T. Ash, Ryan P. Adams. [doi]
• Truthful Data Acquisition via Peer PredictionYiling Chen, Yiheng Shen, Shuran Zheng. [doi]
• From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical ClusteringInes Chami, Albert Gu, Vaggos Chatziafratis, Christopher Ré. [doi]
• RelationNet++: Bridging Visual Representations for Object Detection via Transformer DecoderCheng Chi, Fangyun Wei, Han Hu 0004. [doi]
• Multiparameter Persistence Image for Topological Machine LearningMathieu Carrière, Andrew J. Blumberg. [doi]
• GreedyFool: Distortion-Aware Sparse Adversarial AttackXiaoyi Dong, Dongdong Chen 0001, Jianmin Bao, Chuan Qin, Lu Yuan, Weiming Zhang, Nenghai Yu, Dong Chen. [doi]
• Baxter Permutation ProcessMasahiro Nakano, Akisato Kimura, Takeshi Yamada, Naonori Ueda. [doi]
• Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein DistanceZiv Goldfeld, Kristjan H. Greenewald, Kengo Kato. [doi]
• On the universality of deep learningEmmanuel Abbe, Colin Sandon. [doi]
• Practical No-box Adversarial Attacks against DNNsQizhang Li, Yiwen Guo, Hao Chen. [doi]
• Focus of Attention Improves Information Transfer in Visual FeaturesMatteo Tiezzi, Stefano Melacci, Alessandro Betti, Marco Maggini, Marco Gori. [doi]
• Finding All $\epsilon$-Good Arms in Stochastic BanditsBlake Mason, Lalit Jain, Ardhendu Tripathy, Robert Nowak 0001. [doi]
• A Local Temporal Difference Code for Distributional Reinforcement LearningPablo Tano, Peter Dayan, Alexandre Pouget. [doi]
• No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification ProblemsNimit Sharad Sohoni, Jared Dunnmon, Geoffrey Angus, Albert Gu, Christopher Ré. [doi]
• Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment SearchJaehyeon Kim, Sungwon Kim, Jungil Kong, Sungroh Yoon. [doi]
• Dynamic allocation of limited memory resources in reinforcement learningNisheet Patel, Luigi Acerbi, Alexandre Pouget. [doi]
• CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted InstancesJihoon Tack, Sangwoo Mo, Jongheon Jeong, Jinwoo Shin. [doi]
• Learning Disentangled Representations of Videos with Missing DataArmand Comas Massague, Chi Zhang, Zlatan Feric, Octavia I. Camps, Rose Yu. [doi]
• List-Decodable Mean Estimation via Iterative Multi-FilteringIlias Diakonikolas, Daniel Kane, Daniel Kongsgaard. [doi]
• Discovering conflicting groups in signed networksRuo-Chun Tzeng, Bruno Ordozgoiti, Aristides Gionis. [doi]
• Online Adaptation for Consistent Mesh Reconstruction in the WildXueting Li, Sifei Liu, Shalini De Mello, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang 0001, Jan Kautz. [doi]
• Learning Composable Energy Surrogates for PDE Order ReductionAlex Beatson, Jordan T. Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams. [doi]
• Auxiliary Task Reweighting for Minimum-data LearningBaifeng Shi, Judy Hoffman, Kate Saenko, Trevor Darrell, Huijuan Xu. [doi]
• Beyond Homophily in Graph Neural Networks: Current Limitations and Effective DesignsJiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra. [doi]
• Recurrent Switching Dynamical Systems Models for Multiple Interacting Neural PopulationsJoshua I. Glaser, Matthew Whiteway, John P. Cunningham, Liam Paninski, Scott W. Linderman. [doi]
• Point process models for sequence detection in high-dimensional neural spike trainsAlex H. Williams, Anthony Degleris, Yixin Wang, Scott W. Linderman. [doi]
• Adaptive Discretization for Model-Based Reinforcement LearningSean R. Sinclair, Tianyu Wang, Gauri Jain, Siddhartha Banerjee, Christina Lee Yu. [doi]
• Optimal Epoch Stochastic Gradient Descent Ascent Methods for Min-Max OptimizationYan Yan 0006, Yi Xu, Qihang Lin, Wei Liu 0005, Tianbao Yang. [doi]
• How many samples is a good initial point worth in Low-rank Matrix Recovery?Jialun Zhang, Richard Y. Zhang. [doi]
• Boundary thickness and robustness in learning modelsYaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney. [doi]
• Provably Efficient Exploration for Reinforcement Learning Using Unsupervised LearningFei Feng, Ruosong Wang, Wotao Yin, Simon S. Du, Lin F. Yang. [doi]
• Cross-Scale Internal Graph Neural Network for Image Super-ResolutionShangchen Zhou, Jiawei Zhang, Wangmeng Zuo, Chen Change Loy. [doi]
• Learning Feature Sparse Principal SubspaceLai Tian, Feiping Nie 0001, Rong Wang, Xuelong Li. [doi]
• Reconstructing Perceptive Images from Brain Activity by Shape-Semantic GANTao Fang, Yu Qi, Gang Pan 0001. [doi]
• COT-GAN: Generating Sequential Data via Causal Optimal TransportTianlin Xu, Li Kevin Wenliang, Michael Munn, Beatrice Acciaio. [doi]
• DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANsYaxing Wang, Lu Yu 0004, Joost van de Weijer 0001. [doi]
• GAIT-prop: A biologically plausible learning rule derived from backpropagation of errorNasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni. [doi]
• Organizing recurrent network dynamics by task-computation to enable continual learningLea Duncker, Laura Driscoll, Krishna V. Shenoy, Maneesh Sahani, David Sussillo. [doi]
• Unbalanced Sobolev DescentYoussef Mroueh, Mattia Rigotti. [doi]
• Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement LearningTianren Zhang, Shangqi Guo, Tian Tan 0003, Xiaolin Hu, Feng Chen 0007. [doi]
• Learning Utilities and Equilibria in Non-Truthful AuctionsHu Fu, Tao Lin. [doi]
• Early-Learning Regularization Prevents Memorization of Noisy LabelsSheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda. [doi]
• MetaPoison: Practical General-purpose Clean-label Data PoisoningW. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein. [doi]
• Bootstrapping neural processesJuho Lee, Yoonho Lee, Jungtaek Kim, Eunho Yang, Sung Ju Hwang, Yee Whye Teh. [doi]
• SE(3)-Transformers: 3D Roto-Translation Equivariant Attention NetworksFabian Fuchs, Daniel E. Worrall, Volker Fischer 0003, Max Welling. [doi]
• Reducing Adversarially Robust Learning to Non-Robust PAC LearningOmar Montasser, Steve Hanneke, Nati Srebro. [doi]
• A Robust Functional EM Algorithm for Incomplete Panel Count DataAlexander Moreno, Zhenke Wu, Jamie Yap, Cho Lam, David W. Wetter, Inbal Nahum-Shani, Walter H. Dempsey, James M. Rehg. [doi]
• Model Class Reliance for Random ForestsGavin Smith, Roberto Mansilla, James Goulding. [doi]
• Co-Tuning for Transfer LearningKaichao You, Zhi Kou, Mingsheng Long, Jianmin Wang 0001. [doi]
• BoTorch: A Framework for Efficient Monte-Carlo Bayesian OptimizationMaximilian Balandat, Brian Karrer, Daniel R. Jiang, Samuel Daulton, Benjamin Letham, Andrew Gordon Wilson, Eytan Bakshy. [doi]
• Asymptotically Optimal Exact Minibatch Metropolis-HastingsRuqi Zhang, A. Feder Cooper, Christopher De Sa. [doi]
• Look-ahead Meta Learning for Continual LearningGunshi Gupta, Karmesh Yadav, Liam Paull. [doi]
• The Statistical Cost of Robust Kernel Hyperparameter TurningRaphael Arkady Meyer, Christopher Musco. [doi]
• Deep Relational Topic Modeling via Graph Poisson Gamma Belief NetworkChaojie Wang, Hao Zhang 0050, Bo Chen 0001, Dongsheng Wang, Zhengjue Wang, Mingyuan Zhou. [doi]
• Robust Optimal Transport with Applications in Generative Modeling and Domain AdaptationYogesh Balaji, Rama Chellappa, Soheil Feizi. [doi]
• Diversity-Guided Multi-Objective Bayesian Optimization With Batch EvaluationsMina Konakovic-Lukovic, Yunsheng Tian, Wojciech Matusik. [doi]
• Higher-Order Certification For Randomized SmoothingJeet Mohapatra, Ching Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu 0001, Luca Daniel. [doi]
• Compositional Zero-Shot Learning via Fine-Grained Dense Feature CompositionDat Huynh, Ehsan Elhamifar. [doi]
• Proximal Mapping for Deep RegularizationMao Li, Yingyi Ma, Xinhua Zhang. [doi]
• Online Algorithm for Unsupervised Sequential Selection with Contextual InformationArun Verma, Manjesh Kumar Hanawal, Csaba Szepesvári, Venkatesh Saligrama. [doi]
• Lipschitz Bounds and Provably Robust Training by Laplacian SmoothingVishaal Krishnan, Abed AlRahman Al Makdah, Fabio Pasqualetti. [doi]
• Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter Abbeel. [doi]
• Rewriting History with Inverse RL: Hindsight Inference for Policy ImprovementBen Eysenbach, Xinyang Geng, Sergey Levine, Russ R. Salakhutdinov. [doi]
• Continual Deep Learning by Functional Regularisation of Memorable PastPingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard E. Turner, Mohammad Emtiyaz Khan. [doi]
• Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision ProcessesYuval Emek, Ron Lavi, Rad Niazadeh, Yangguang Shi. [doi]
• Pontryagin Differentiable Programming: An End-to-End Learning and Control FrameworkWanxin Jin, Zhaoran Wang, Zhuoran Yang, Shaoshuai Mou. [doi]
• Compositional Explanations of NeuronsJesse Mu, Jacob Andreas. [doi]
• AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed GradientsJuntang Zhuang, Tommy Tang, Yifan Ding, Sekhar C. Tatikonda, Nicha C. Dvornek, Xenophon Papademetris, James S. Duncan. [doi]
• Dynamic Regret of Policy Optimization in Non-Stationary EnvironmentsYingjie Fei, Zhuoran Yang, Zhaoran Wang, Qiaomin Xie. [doi]
• A Fair Classifier Using Kernel Density EstimationJaewoong Cho, Gyeongjo Hwang, Changho Suh. [doi]
• CircleGAN: Generative Adversarial Learning across Spherical CirclesWoohyeon Shim, Minsu Cho. [doi]
• Evolving Graphical Planner: Contextual Global Planning for Vision-and-Language NavigationZhiwei Deng, Karthik Narasimhan, Olga Russakovsky. [doi]
• Small Nash Equilibrium Certificates in Very Large GamesBrian Hu Zhang, Tuomas Sandholm. [doi]
• The Cone of Silence: Speech Separation by LocalizationTeerapat Jenrungrot, Vivek Jayaram, Steve Seitz, Ira Kemelmacher-Shlizerman. [doi]
• Multi-agent Trajectory Prediction with Fuzzy Query AttentionNitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang 0004, Yan Liu 0002. [doi]
• Approximate Cross-Validation for Structured ModelsSoumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer Deshpande, Tamara Broderick. [doi]
• Learning to Play Sequential Games versus Unknown OpponentsPier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause 0001. [doi]
• CoSE: Compositional Stroke EmbeddingsEmre Aksan, Thomas Deselaers, Andrea Tagliasacchi, Otmar Hilliges. [doi]
• Teaching a GAN What Not to LearnSiddarth Asokan, Chandra Sekhar Seelamantula. [doi]
• Predictive inference is free with the jackknife+-after-bootstrapByol Kim, Chen Xu, Rina Foygel Barber. [doi]
• Assisted Learning: A Framework for Multi-Organization LearningXun Xian, Xinran Wang, Jie Ding 0002, Reza Ghanadan. [doi]
• Better Full-Matrix Regret via Parameter-Free Online LearningAshok Cutkosky. [doi]
• Bi-level Score Matching for Learning Energy-based Latent Variable ModelsFan Bao, Chongxuan Li, Taufik Xu, Hang Su 0006, Jun Zhu 0001, Bo Zhang 0010. [doi]
• Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous VariablesGuangyao Zhou. [doi]
• Non-Convex SGD Learns Halfspaces with Adversarial Label NoiseIlias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis. [doi]
• Second Order PAC-Bayesian Bounds for the Weighted Majority VoteAndrés R. Masegosa, Stephan Sloth Lorenzen, Christian Igel, Yevgeny Seldin. [doi]
• Factorized Neural Processes for Neural Processes: K-Shot Prediction of Neural ResponsesRonald (James) Cotton, Fabian H. Sinz, Andreas S. Tolias. [doi]
• Probabilistic Linear Solvers for Machine LearningJonathan Wenger, Philipp Hennig. [doi]
• Optimal Prediction of the Number of Unseen Species with MultiplicityYi Hao, Ping Li 0001. [doi]
• The Advantage of Conditional Meta-Learning for Biased Regularization and Fine TuningGiulia Denevi, Massimiliano Pontil, Carlo Ciliberto. [doi]
• Learning Physical Graph Representations from Visual ScenesDaniel Bear, Chaofei Fan, Damian Mrowca, Yunzhu Li, Seth Alter, Aran Nayebi, Jeremy Schwartz, Li Fei-Fei 0001, Jiajun Wu 0001, Josh Tenenbaum 0001, Daniel L. Yamins. [doi]
• On Efficiency in Hierarchical Reinforcement LearningZheng Wen, Doina Precup, Morteza Ibrahimi, André Barreto, Benjamin Van Roy, Satinder Singh. [doi]
• Modern Hopfield Networks and Attention for Immune Repertoire ClassificationMichael Widrich, Bernhard Schäfl, Milena Pavlovic, Hubert Ramsauer, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer. [doi]
• Parabolic Approximation Line Search for DNNsMaximus Mutschler, Andreas Zell. [doi]
• What went wrong and when? Instance-wise feature importance for time-series black-box modelsSana Tonekaboni, Shalmali Joshi, Kieran Campbell, David Duvenaud, Anna Goldenberg. [doi]
• Quantized Variational InferenceAmir Dib. [doi]
• Logarithmic Regret Bound in Partially Observable Linear Dynamical SystemsSahin Lale, Kamyar Azizzadenesheli, Babak Hassibi, Anima Anandkumar. [doi]
• Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial SettingsPantelis Elinas, Edwin V. Bonilla, Louis C. Tiao. [doi]
• Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase TransitionLin Chen, Qian Yu 0001, Hannah Lawrence, Amin Karbasi. [doi]
• Blind Video Temporal Consistency via Deep Video PriorChenyang Lei, Yazhou Xing, Qifeng Chen. [doi]
• Provably Efficient Neural Estimation of Structural Equation Models: An Adversarial ApproachLuofeng Liao, You-Lin Chen, Zhuoran Yang, Bo Dai, Mladen Kolar, Zhaoran Wang. [doi]
• Deep Shells: Unsupervised Shape Correspondence with Optimal TransportMarvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers. [doi]
• KFC: A Scalable Approximation Algorithm for $k$-center Fair ClusteringElfarouk Harb, Ho Shan Lam. [doi]
• Online Learning in Contextual Bandits using Gated Linear NetworksEren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness. [doi]
• Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex OptimizationXuefeng Gao, Mert Gürbüzbalaban, Lingjiong Zhu. [doi]
• Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent SamplingTong Che, Ruixiang Zhang, Jascha Sohl-Dickstein, Hugo Larochelle, Liam Paull, Yuan Cao, Yoshua Bengio. [doi]
• Rethinking Learnable Tree Filter for Generic Feature TransformLin Song, Yanwei Li, Zhengkai Jiang, Zeming Li, Xiangyu Zhang 0005, Hongbin Sun 0001, Jian Sun 0015, Nanning Zheng 0001. [doi]
• Locally-Adaptive Nonparametric Online LearningIlja Kuzborskij, Nicolò Cesa-Bianchi. [doi]
• Sparse Learning with CARTJason Klusowski. [doi]
• Network-to-Network Translation with Conditional Invertible Neural NetworksRobin Rombach, Patrick Esser, Björn Ommer. [doi]
• Unifying Activation- and Timing-based Learning Rules for Spiking Neural NetworksJinseok Kim 0004, Kyungsu Kim, Jae-Joon Kim. [doi]
• Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped ObservationsAlexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott. [doi]
• Learning discrete distributions: user vs item-level privacyYuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley 0001. [doi]
• Understanding Deep Architecture with Reasoning LayerXinshi Chen, Yufei Zhang, Christoph Reisinger, Le Song. [doi]
• Offline Imitation Learning with a Misspecified SimulatorShengyi Jiang, Jing-Cheng Pang, Yang Yu 0001. [doi]
• A Causal View on Robustness of Neural NetworksCheng Zhang 0005, Kun Zhang, Yingzhen Li. [doi]
• Matérn Gaussian Processes on Riemannian ManifoldsViacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth. [doi]
• Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank AssumptionsHayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi. [doi]
• Towards Crowdsourced Training of Large Neural Networks using Decentralized Mixture-of-ExpertsMax Ryabinin, Anton Gusev. [doi]
• MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and NumericsLuca De Gennaro Aquino, Stephan Eckstein. [doi]
• Dark Experience for General Continual Learning: a Strong, Simple BaselinePietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, Simone Calderara. [doi]
• ExpandNets: Linear Over-parameterization to Train Compact Convolutional NetworksShuxuan Guo, Jose M. Alvarez, Mathieu Salzmann. [doi]
• STEER : Simple Temporal Regularization For Neural ODEArnab Ghosh, Harkirat S. Behl, Emilien Dupont, Philip H. S. Torr, Vinay Namboodiri. [doi]
• Flexible mean field variational inference using mixtures of non-overlapping exponential familiesJeffrey P. Spence. [doi]
• On Adaptive Attacks to Adversarial Example DefensesFlorian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry. [doi]
• Rethinking pooling in graph neural networksDiego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski. [doi]
• Calibrating Deep Neural Networks using Focal LossJishnu Mukhoti, Viveka Kulharia, Amartya Sanyal, Stuart Golodetz, Philip H. S. Torr, Puneet K. Dokania. [doi]
• Biological credit assignment through dynamic inversion of feedforward networksWilliam F. Podlaski, Christian K. Machens. [doi]
• Learning to Learn Variational Semantic MemoryXiantong Zhen, Ying-jun Du, Huan Xiong, Qiang Qiu, Cees Snoek, Ling Shao 0001. [doi]
• Supervised Contrastive LearningPrannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan. [doi]
• Online Learning with Primary and Secondary LossesAvrim Blum, Han Shao. [doi]
• Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian OptimizationSamuel Daulton, Maximilian Balandat, Eytan Bakshy. [doi]
• GNNGuard: Defending Graph Neural Networks against Adversarial AttacksXiang Zhang, Marinka Zitnik. [doi]
• Gradient-EM Bayesian Meta-LearningYayi Zou, Xiaoqi Lu. [doi]
• Prediction with Corrupted Expert AdviceIdan Amir, Idan Attias, Tomer Koren, Yishay Mansour, Roi Livni. [doi]
• An Efficient Adversarial Attack for Tree EnsemblesChong Zhang, Huan Zhang 0001, Cho-Jui Hsieh. [doi]
• Adaptive Learning of Rank-One Models for Efficient Pairwise Sequence AlignmentGovinda M. Kamath, Tavor Z. Baharav, Ilan Shomorony. [doi]
• Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language ProcessingZihang Dai, Guokun Lai, Yiming Yang, Quoc Le 0001. [doi]
• A Dynamical Central Limit Theorem for Shallow Neural NetworksZhengdao Chen, Grant M. Rotskoff, Joan Bruna, Eric Vanden-Eijnden. [doi]
• Secretary and Online Matching Problems with Machine Learned AdviceAntonios Antoniadis, Themis Gouleakis, Pieter Kleer, Pavel Kolev. [doi]
• The NetHack Learning EnvironmentHeinrich Küttler, Nantas Nardelli, Alexander H. Miller, Roberta Raileanu, Marco Selvatici, Edward Grefenstette, Tim Rocktäschel. [doi]
• Rotated Binary Neural NetworkMingbao Lin, Rongrong Ji, Zihan Xu, Baochang Zhang 0001, Yan Wang 0059, Yongjian Wu, Feiyue Huang, Chia-Wen Lin. [doi]
• Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree SearchLinnan Wang, Rodrigo Fonseca, Yuandong Tian. [doi]
• PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural NetworksMinh N. Vu, My T. Thai. [doi]
• On the training dynamics of deep networks with $L_2$ regularizationAitor Lewkowycz, Guy Gur-Ari. [doi]
• Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence RateAkifumi Okuno, Hidetoshi Shimodaira. [doi]
• The Mean-Squared Error of Double Q-LearningWentao Weng, Harsh Gupta, Niao He, Lei Ying, R. Srikant 0001. [doi]
• Structured Prediction for Conditional Meta-LearningRuohan Wang, Yiannis Demiris, Carlo Ciliberto. [doi]
• Non-parametric Models for Non-negative FunctionsUlysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi. [doi]
• Learning sparse codes from compressed representations with biologically plausible local wiring constraintsKion Fallah, Adam Willats, Ninghao Liu, Christopher Rozell. [doi]
• Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and DelayJoão Marques-Silva 0001, Thomas Gerspacher, Martin C. Cooper, Alexey Ignatiev, Nina Narodytska. [doi]
• CO-Optimal TransportTitouan Vayer, Ievgen Redko, Rémi Flamary, Nicolas Courty. [doi]
• Stability of Stochastic Gradient Descent on Nonsmooth Convex LossesRaef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar. [doi]
• Multi-Task Reinforcement Learning with Soft ModularizationRuihan Yang, Huazhe Xu, Yi Wu, Xiaolong Wang. [doi]
• Adversarial Style Mining for One-Shot Unsupervised Domain AdaptationYawei Luo, Ping Liu, Tao Guan, Junqing Yu, Yi Yang 0001. [doi]
• User-Dependent Neural Sequence Models for Continuous-Time Event DataAlex Boyd, Robert Bamler, Stephan Mandt, Padhraic Smyth. [doi]
• Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose trackingAnqi Wu, Estefany Kelly Buchanan, Matthew Whiteway, Michael Schartner, Guido Meijer, Jean-Paul Noel, Erica Rodriguez, Claire Everett, Amy Norovich, Evan Schaffer, Neeli Mishra, C. Daniel Salzman, Dora Angelaki, Andrés Bendesky, International Brain Laboratory, John P. Cunningham, Liam Paninski. [doi]
• Autofocused oracles for model-based designClara Fannjiang, Jennifer Listgarten. [doi]
• Approximate Cross-Validation with Low-Rank Data in High DimensionsWilliam T. Stephenson, Madeleine Udell, Tamara Broderick. [doi]
• A Limitation of the PAC-Bayes FrameworkRoi Livni, Shay Moran. [doi]
• RSKDD-Net: Random Sample-based Keypoint Detector and DescriptorFan Lu, Guang Chen 0001, YinLong Liu, Zhongnan Qu, Alois C. Knoll. [doi]
• High-contrast "gaudy" images improve the training of deep neural network models of visual cortexBenjamin Cowley 0002, Jonathan W. Pillow. [doi]
• A Spectral Energy Distance for Parallel Speech SynthesisAlexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner. [doi]
• Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on GraphsNikolaos Karalias, Andreas Loukas. [doi]
• A Stochastic Path Integral Differential EstimatoR Expectation Maximization AlgorithmGersende Fort, Eric Moulines, Hoi-To Wai. [doi]
• Randomized tests for high-dimensional regression: A more efficient and powerful solutionYue Li, Ilmun Kim, Yuting Wei. [doi]
• The Primal-Dual method for Learning Augmented AlgorithmsÉtienne Bamas, Andreas Maggiori, Ola Svensson. [doi]
• HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural NetworksZhen Dong, Zhewei Yao, Daiyaan Arfeen, Amir Gholami, Michael W. Mahoney, Kurt Keutzer. [doi]
• GradAug: A New Regularization Method for Deep Neural NetworksTaojiannan Yang, Sijie Zhu, Chen Chen 0001. [doi]
• All your loss are belong to BayesChristian J. Walder, Richard Nock. [doi]
• On ranking via sorting by estimated expected utilityClément Calauzènes, Nicolas Usunier. [doi]
• Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterizationChong You, Zhihui Zhu, Qing Qu, Yi Ma. [doi]
• Learning to summarize with human feedbackNisan Stiennon, Long Ouyang, Jeffrey Wu 0003, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, Paul F. Christiano. [doi]
• Auto Learning AttentionBenteng Ma, Jing Zhang, Yong Xia, Dacheng Tao. [doi]
• Space-Time Correspondence as a Contrastive Random WalkAllan Jabri, Andrew Owens, Alexei A. Efros. [doi]
• Meta-Learning with Adaptive HyperparametersSungyong Baik, Myungsub Choi, Janghoon Choi, Heewon Kim, Kyoung Mu Lee. [doi]
• Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector MachineJiajin Li, Caihua Chen, Anthony Man-Cho So. [doi]
• Towards Scalable Bayesian Learning of Causal DAGsJussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto. [doi]
• Differentiable Meta-Learning of Bandit PoliciesCraig Boutilier, Chih-Wei Hsu, Branislav Kveton, Martin Mladenov, Csaba Szepesvári, Manzil Zaheer. [doi]
• Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex ModelsTom Heskes, Evi Sijben, Ioan Gabriel Bucur, Tom Claassen. [doi]
• Adapting Neural Architectures Between DomainsYanxi Li, Zhaohui Yang, Yunhe Wang, Chang Xu 0002. [doi]
• Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian ProcessesHao Chen, Lili Zheng, Raed Al Kontar, Garvesh Raskutti. [doi]
• Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient ClippingEduard A. Gorbunov, Marina Danilova, Alexander Gasnikov. [doi]
• 1 RegularizationMasaaki Takada, Hironori Fujisawa. [doi]
• Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative ModelGen Li 0005, Yuting Wei, Yuejie Chi, Yuantao Gu, Yuxin Chen 0002. [doi]
• Sample Complexity of Uniform Convergence for MulticalibrationEliran Shabat, Lee Cohen, Yishay Mansour. [doi]
• Fictitious Play for Mean Field Games: Continuous Time Analysis and ApplicationsSarah Perrin, Julien Pérolat, Mathieu Laurière, Matthieu Geist, Romuald Elie, Olivier Pietquin. [doi]
• Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised LearningZhongzheng Ren, Raymond A. Yeh, Alexander G. Schwing. [doi]
• Generalised Bayesian Filtering via Sequential Monte CarloAyman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen. [doi]
• The Autoencoding Variational AutoencoderTaylan Cemgil, Sumedh Ghaisas, Krishnamurthy Dvijotham, Sven Gowal, Pushmeet Kohli. [doi]
• The Strong Screening Rule for SLOPEJohan Larsson 0002, Malgorzata Bogdan, Jonas Wallin. [doi]
• Asymptotic normality and confidence intervals for derivatives of 2-layers neural network in the random features modelYiwei Shen, Pierre C. Bellec. [doi]
• Learning to Adapt to Evolving DomainsHong Liu, Mingsheng Long, Jianmin Wang, Yu Wang. [doi]
• Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG PredictionMariya Toneva, Otilia Stretcu, Barnabás Póczos, Leila Wehbe, Tom M. Mitchell. [doi]
• Causal analysis of Covid-19 Spread in GermanyAtalanti-Anastasia Mastakouri, Bernhard Schölkopf. [doi]
• ICNet: Intra-saliency Correlation Network for Co-Saliency DetectionWenda Jin, Jun Xu 0019, Ming-Ming Cheng, Yi Zhang, Wei Guo. [doi]
• PEP: Parameter Ensembling by PerturbationAlireza Mehrtash, Purang Abolmaesumi, Polina Golland, Tina Kapur, Demian Wassermann, William Wells. [doi]
• Learning Strategy-Aware Linear ClassifiersYiling Chen, Yang Liu 0018, Chara Podimata. [doi]
• Belief-Dependent Macro-Action Discovery in POMDPs using the Value of InformationGenevieve Flaspohler, Nicholas A. Roy, John W. Fisher III. [doi]
• DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian NetworksDennis Wei, Tian Gao, Yue Yu. [doi]
• Ensuring Fairness Beyond the Training DataDebmalya Mandal, Samuel Deng, Suman Jana, Jeannette M. Wing, Daniel J. Hsu. [doi]
• Cooperative Multi-player Bandit OptimizationIlai Bistritz, Nicholas Bambos. [doi]
• SOLOv2: Dynamic and Fast Instance SegmentationXinlong Wang, Rufeng Zhang, Tao Kong, Lei Li, Chunhua Shen. [doi]
• Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence AnalysisShaocong Ma, Yi Zhou, Shaofeng Zou. [doi]
• Learning Discrete Energy-based Models via Auxiliary-variable Local ExplorationHanjun Dai, Rishabh Singh, Bo Dai, Charles Sutton, Dale Schuurmans. [doi]
• An Efficient Asynchronous Method for Integrating Evolutionary and Gradient-based Policy SearchKyunghyun Lee 0004, Byeong-uk Lee, Ukcheol Shin, In-So Kweon. [doi]
• Learning Optimal Representations with the Decodable Information BottleneckYann Dubois, Douwe Kiela, David J. Schwab, Ramakrishna Vedantam. [doi]
• All Word Embeddings from One EmbeddingSho Takase, Sosuke Kobayashi. [doi]
• Backpropagating Linearly Improves Transferability of Adversarial ExamplesYiwen Guo, Qizhang Li, Hao Chen. [doi]
• Mitigating Manipulation in Peer Review via Randomized Reviewer AssignmentsSteven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang. [doi]
• Partially View-aligned ClusteringZhenyu Huang, Peng Hu 0002, Joey Tianyi Zhou, Jiancheng Lv, Xi Peng 0001. [doi]
• Collegial EnsemblesEtai Littwin, Ben Myara, Sima Sabah, Joshua M. Susskind, Shuangfei Zhai, Oren Golan. [doi]
• Consistent Plug-in Classifiers for Complex Objectives and ConstraintsShiv Kumar Tavker, Harish Guruprasad Ramaswamy, Harikrishna Narasimhan. [doi]
• Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture DistributionsMatthew Faw, Rajat Sen, Karthikeyan Shanmugam, Constantine Caramanis, Sanjay Shakkottai. [doi]
• Faster DBSCAN via subsampled similarity queriesHeinrich Jiang, Jennifer Jang, Jakub Lacki. [doi]
• Sharpened Generalization Bounds based on Conditional Mutual Information and an Application to Noisy, Iterative AlgorithmsMahdi Haghifam, Jeffrey Negrea, Ashish Khisti, Daniel M. Roy 0001, Gintare Karolina Dziugaite. [doi]
• Coded Sequential Matrix Multiplication For Straggler MitigationM. Nikhil Krishnan, Seyederfan Hosseini, Ashish Khisti. [doi]
• Information Theoretic Counterfactual Learning from Missing-Not-At-Random FeedbackZifeng Wang, Xi Chen, Rui Wen, Shao-Lun Huang, Ercan E. Kuruoglu, Yefeng Zheng. [doi]
• On Completeness-aware Concept-Based Explanations in Deep Neural NetworksChih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Tomas Pfister, Pradeep Ravikumar. [doi]
• Convex optimization based on global lower second-order modelsNikita Doikov, Yurii E. Nesterov. [doi]
• Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom methodMichal Derezinski, Rajiv Khanna, Michael W. Mahoney. [doi]
• Inductive Quantum EmbeddingSantosh K. Srivastava, Dinesh Khandelwal, Dhiraj Madan, Dinesh Garg, Hima Karanam, L. Venkata Subramaniam. [doi]
• Compositional Visual Generation with Energy Based ModelsYilun Du, Shuang Li, Igor Mordatch. [doi]
• Compact task representations as a normative model for higher-order brain activitySeverin Berger, Christian K. Machens. [doi]
• Rethinking Pre-training and Self-trainingBarret Zoph, Golnaz Ghiasi, Tsung-Yi Lin, Yin Cui, Hanxiao Liu, Ekin Dogus Cubuk, Quoc Le 0001. [doi]
• MRI Banding Removal via Adversarial TrainingAaron Defazio, Tullie Murrell, Michael P. Recht. [doi]
• Make One-Shot Video Object Segmentation Efficient AgainTim Meinhardt, Laura Leal-Taixé. [doi]
• Inverse Rational Control with Partially Observable Continuous Nonlinear DynamicsMinhae Kwon, Saurabh Daptardar, Paul R. Schrater, Zachary Pitkow. [doi]
• MOReL: Model-Based Offline Reinforcement LearningRahul Kidambi, Aravind Rajeswaran, Praneeth Netrapalli, Thorsten Joachims. [doi]
• Semantic Visual Navigation by Watching YouTube VideosMatthew Chang, Arjun Gupta, Saurabh Gupta. [doi]
• A Novel Approach for Constrained Optimization in Graphical ModelsSara Rouhani, Tahrima Rahman, Vibhav Gogate. [doi]
• GCN meets GPU: Decoupling "When to Sample" from "How to Sample"Morteza Ramezani, Weilin Cong, Mehrdad Mahdavi, Anand Sivasubramaniam, Mahmut T. Kandemir. [doi]
• Doubly Robust Off-Policy Value and Gradient Estimation for Deterministic PoliciesNathan Kallus, Masatoshi Uehara. [doi]
• Sinkhorn Barycenter via Functional Gradient DescentZebang Shen, Zhenfu Wang, Alejandro Ribeiro, Hamed Hassani. [doi]
• Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning​Shreyas Fadnavis, Joshua Batson, Eleftherios Garyfallidis. [doi]
• Outlier Robust Mean Estimation with Subgaussian Rates via StabilityIlias Diakonikolas, Daniel M. Kane, Ankit Pensia. [doi]
• Adaptive Sampling for Stochastic Risk-Averse LearningSebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause 0001. [doi]
• Efficient Distance Approximation for Structured High-Dimensional Distributions via LearningArnab Bhattacharyya 0001, Sutanu Gayen, Kuldeep S. Meel, N. V. Vinodchandran. [doi]
• Election Coding for Distributed Learning: Protecting SignSGD against Byzantine AttacksJy-yong Sohn, Dong-Jun Han, Beongjun Choi, Jaekyun Moon. [doi]
• Instance Based Approximations to Profile Maximum LikelihoodNima Anari, Moses Charikar, Kirankumar Shiragur, Aaron Sidford. [doi]
• Set2Graph: Learning Graphs From SetsHadar Serviansky, Nimrod Segol, Jonathan Shlomi, Kyle Cranmer, Eilam Gross, Haggai Maron, Yaron Lipman. [doi]
• Deep Transformers with Latent DepthXian Li, Asa Cooper Stickland, Yuqing Tang, Xiang Kong. [doi]
• Agree to Disagree: Adaptive Ensemble Knowledge Distillation in Gradient SpaceShangchen Du, Shan You, Xiaojie Li, Jianlong Wu, Fei Wang 0032, Chen Qian 0006, Changshui Zhang. [doi]
• Data Diversification: A Simple Strategy For Neural Machine TranslationXuan-Phi Nguyen, Shafiq R. Joty, Kui Wu, Ai Ti Aw. [doi]
• Self-Paced Deep Reinforcement LearningPascal Klink, Carlo D'Eramo, Jan Peters 0001, Joni Pajarinen. [doi]
• Language Through a Prism: A Spectral Approach for Multiscale Language RepresentationsAlex Tamkin, Dan Jurafsky, Noah D. Goodman. [doi]
• Escaping Saddle-Point Faster under Interpolation-like ConditionsAbhishek Roy 0005, Krishnakumar Balasubramanian, Saeed Ghadimi, Prasant Mohapatra. [doi]
• Statistical-Query Lower Bounds via Functional GradientsSurbhi Goel, Aravind Gollakota, Adam R. Klivans. [doi]
• Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax GamesArun Sai Suggala, Praneeth Netrapalli. [doi]
• Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear ProgramsAgniva Chowdhury, Palma London, Haim Avron, Petros Drineas. [doi]
• Stationary Activations for Uncertainty Calibration in Deep LearningLassi Meronen, Christabella Irwanto, Arno Solin. [doi]
• Design Space for Graph Neural NetworksJiaxuan You, Zhitao Ying, Jure Leskovec. [doi]
• Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based GamesYunqiu Xu, Meng Fang, Ling Chen 0006, Yali Du, Joey Tianyi Zhou, Chengqi Zhang. [doi]
• On Power Laws in Deep EnsemblesEkaterina Lobacheva, Nadezhda Chirkova, Maxim Kodryan, Dmitry P. Vetrov. [doi]
• Adaptive Graph Convolutional Recurrent Network for Traffic ForecastingLei Bai 0001, Lina Yao, Can Li, Xianzhi Wang 0001, Can Wang 0004. [doi]
• Towards More Practical Adversarial Attacks on Graph Neural NetworksJiaqi Ma 0001, Shuangrui Ding, Qiaozhu Mei. [doi]
• Understanding Global Feature Contributions With Additive Importance MeasuresIan Covert, Scott M. Lundberg, Su-In Lee. [doi]
• Optimal Best-arm Identification in Linear BanditsYassir Jedra, Alexandre Proutière. [doi]
• Curriculum Learning by Dynamic Instance HardnessTianyi Zhou, Shengjie Wang, Jeff A. Bilmes. [doi]
• Learning Differential Equations that are Easy to SolveJacob Kelly, Jesse Bettencourt, Matthew J. Johnson 0002, David Duvenaud. [doi]
• Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainabilityChristopher Frye, Colin Rowat, Ilya Feige. [doi]
• Federated Bayesian Optimization via Thompson SamplingZhongxiang Dai, Bryan Kian Hsiang Low, Patrick Jaillet. [doi]
• PAC-Bayes Analysis Beyond the Usual BoundsOmar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor. [doi]
• Self-Distillation Amplifies Regularization in Hilbert SpaceHossein Mobahi, Mehrdad Farajtabar, Peter L. Bartlett. [doi]
• Black-Box Ripper: Copying black-box models using generative evolutionary algorithmsAntonio Barbalau, Adrian Cosma, Radu-Tudor Ionescu, Marius Popescu. [doi]
• General Transportability of Soft Interventions: Completeness ResultsJuan D. Correa, Elias Bareinboim. [doi]
• An implicit function learning approach for parametric modal regressionYangchen Pan, Ehsan Imani, Amir Massoud Farahmand, Martha White. [doi]
• Fully Dynamic Algorithm for Constrained Submodular OptimizationSilvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakub Tarnawski, Morteza Zadimoghaddam. [doi]
• Replica-Exchange Nosé-Hoover Dynamics for Bayesian Learning on Large DatasetsRui Luo, Qiang Zhang, Yaodong Yang, Jun Wang 0012. [doi]
• Neuron-level Structured Pruning using Polarization RegularizerTao Zhuang, Zhixuan Zhang, Yuheng Huang, Xiaoyi Zeng, Kai Shuang, Xiang Li. [doi]
• Exemplar Guided Active LearningJason S. Hartford, Kevin Leyton-Brown, Hadas Raviv, Dan Padnos, Shahar Lev, Barak Lenz. [doi]
• Closing the Dequantization Gap: PixelCNN as a Single-Layer FlowDidrik Nielsen, Ole Winther. [doi]
• On the Theory of Transfer Learning: The Importance of Task DiversityNilesh Tripuraneni, Michael I. Jordan, Chi Jin. [doi]
• Towards Understanding Hierarchical Learning: Benefits of Neural RepresentationsMinshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher. [doi]
• Learning abstract structure for drawing by efficient motor program inductionLucas Y. Tian, Kevin Ellis, Marta Kryven, Josh Tenenbaum 0001. [doi]
• Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language GroundingZhu Zhang, Zhou Zhao, Zhijie Lin, Jieming Zhu, Xiuqiang He. [doi]
• Precise expressions for random projections: Low-rank approximation and randomized NewtonMichal Derezinski, Feynman T. Liang, Zhenyu Liao, Michael W. Mahoney. [doi]
• Thunder: a Fast Coordinate Selection Solver for Sparse LearningShaogang Ren, Weijie Zhao, Ping Li 0001. [doi]
• Multi-Fidelity Bayesian Optimization via Deep Neural NetworksShibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe. [doi]
• Counterfactual Prediction for Bundle TreatmentHao Zou, Peng Cui 0001, Bo Li 0064, Zheyan Shen, Jianxin Ma, Hongxia Yang, Yue He. [doi]
• Meta-Learning Requires Meta-AugmentationJanarthanan Rajendran, Alexander Irpan, Eric Jang. [doi]
• Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic ViewChristos Thrampoulidis, Samet Oymak, Mahdi Soltanolkotabi. [doi]
• When Do Neural Networks Outperform Kernel Methods?Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari. [doi]
• Fast, Accurate, and Simple Models for Tabular Data via Augmented DistillationRasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola. [doi]
• Trust the Model When It Is Confident: Masked Model-based Actor-CriticFeiyang Pan, Jia He, Dandan Tu, Qing He 0003. [doi]
• Reinforcement Learning with Combinatorial Actions: An Application to Vehicle RoutingArthur Delarue, Ross Anderson, Christian Tjandraatmadja. [doi]
• SuperLoss: A Generic Loss for Robust Curriculum LearningThibault Castells, Philippe Weinzaepfel, Jérôme Revaud. [doi]
• ContraGAN: Contrastive Learning for Conditional Image GenerationMinguk Kang, Jaesik Park. [doi]
• Neural Anisotropy DirectionsGuillermo Ortiz-Jiménez, Apostolos Modas, Seyed-Mohsen Moosavi-Dezfooli, Pascal Frossard. [doi]
• Stochastic Optimization for Performative PredictionCelestine Mendler-Dünner, Juan C. Perdomo, Tijana Zrnic, Moritz Hardt. [doi]
• Causal Intervention for Weakly-Supervised Semantic SegmentationDong Zhang, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua 0001, Qianru Sun. [doi]
• RepPoints v2: Verification Meets Regression for Object DetectionYihong Chen, Zheng Zhang 0022, Yue Cao 0001, Liwei Wang, Stephen Lin, Han Hu 0004. [doi]
• Adversarial Attacks on Linear Contextual BanditsEvrard Garcelon, Baptiste Rozière, Laurent Meunier, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta. [doi]
• Deep Transformation-Invariant ClusteringTom Monnier, Thibault Groueix, Mathieu Aubry. [doi]
• Emergent Reciprocity and Team Formation from Randomized Uncertain Social PreferencesBowen Baker. [doi]
• Learning Deep Attribution Priors Based On Prior KnowledgeEthan Weinberger, Joseph D. Janizek, Su-In Lee. [doi]
• Finer Metagenomic Reconstruction via Biodiversity OptimizationSimon Foucart, David Koslicki. [doi]
• Evolving Normalization-Activation LayersHanxiao Liu, Andy Brock, Karen Simonyan, Quoc Le 0001. [doi]
• LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-resolution and BeyondWenbo Li, Kun Zhou, Lu Qi, Nianjuan Jiang, Jiangbo Lu, Jiaya Jia. [doi]
• Efficient Marginalization of Discrete and Structured Latent Variables via SparsityGonçalo M. Correia, Vlad Niculae, Wilker Aziz, André F. T. Martins. [doi]
• Gradient Surgery for Multi-Task LearningTianhe Yu, Saurabh Kumar, Abhishek Gupta 0004, Sergey Levine, Karol Hausman, Chelsea Finn. [doi]
• HOI Analysis: Integrating and Decomposing Human-Object InteractionYong-Lu Li, Xinpeng Liu, Xiaoqian Wu, Yizhuo Li, Cewu Lu. [doi]
• Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture SearchHouwen Peng, Hao Du, Hongyuan Yu, Qi Li, Jing Liao 0001, Jianlong Fu. [doi]
• An efficient nonconvex reformulation of stagewise convex optimization problemsRudy Bunel, Oliver Hinder, Srinadh Bhojanapalli, Krishnamurthy Dvijotham. [doi]
• Benchmarking Deep Learning Interpretability in Time Series PredictionsAya Abdelsalam Ismail, Mohamed K. Gunady, Héctor Corrada Bravo, Soheil Feizi. [doi]
• Towards a Combinatorial Characterization of Bounded-Memory LearningAlon Gonen, Shachar Lovett, Michal Moshkovitz. [doi]
• Directional convergence and alignment in deep learningZiwei Ji, Matus Telgarsky. [doi]
• Monotone operator equilibrium networksEzra Winston, J. Zico Kolter. [doi]
• BOSS: Bayesian Optimization over String SpacesHenry B. Moss, David S. Leslie, Daniel Beck, Javier Gonzalez, Paul Rayson. [doi]
• CoinPress: Practical Private Mean and Covariance EstimationSourav Biswas, Yihe Dong, Gautam Kamath 0001, Jonathan R. Ullman. [doi]
• Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMCArun Ganesh, Kunal Talwar. [doi]
• Contrastive Learning with Adversarial ExamplesChih-Hui Ho, Nuno Nvasconcelos. [doi]
• Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu 0003, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei. [doi]
• Ultra-Low Precision 4-bit Training of Deep Neural NetworksXiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan. [doi]
• Understanding Double Descent Requires A Fine-Grained Bias-Variance DecompositionBen Adlam, Jeffrey Pennington. [doi]
• A Variational Approach for Learning from Positive and Unlabeled DataHui Chen, Fangqing Liu, Yin Wang, Liyue Zhao, Hao Wu. [doi]
• RetroXpert: Decompose Retrosynthesis Prediction Like A ChemistChaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu 0010, JunZhou Huang. [doi]
• Neural Non-Rigid TrackingAljaz Bozic, Pablo R. Palafox, Michael Zollhöfer, Angela Dai, Justus Thies, Matthias Nießner. [doi]
• Succinct and Robust Multi-Agent Communication With Temporal Message ControlSai Qian Zhang, Qi Zhang, Jieyu Lin. [doi]
• On the Similarity between the Laplace and Neural Tangent KernelsAmnon Geifman, Abhay Kumar Yadav, Yoni Kasten, Meirav Galun, David W. Jacobs, Ronen Basri. [doi]
• Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax ProblemsLuo Luo, Haishan Ye, Zhichao Huang, Tong Zhang 0001. [doi]
• Explainable VotingDominik Peters, Ariel D. Procaccia, Alexandros Psomas, Zixin Zhou. [doi]
• Self-Supervised Visual Representation Learning from Hierarchical GroupingXiao Zhang, Michael Maire. [doi]
• FleXOR: Trainable Fractional QuantizationDongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun. [doi]
• Optimizing Mode Connectivity via Neuron AlignmentN. Joseph Tatro, Pin-Yu Chen, Payel Das, Igor Melnyk, Prasanna Sattigeri, Rongjie Lai. [doi]
• Certified Robustness of Graph Convolution Networks for Graph Classification under Topological AttacksHongwei Jin, Zhan Shi, Venkata Jaya Shankar Ashish Peruri, Xinhua Zhang. [doi]
• Online learning with dynamics: A minimax perspectiveKush Bhatia, Karthik Sridharan. [doi]
• How does This Interaction Affect Me? Interpretable Attribution for Feature InteractionsMichael Tsang, Sirisha Rambhatla, Yan Liu 0002. [doi]
• Robust, Accurate Stochastic Optimization for Variational InferenceAkash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen, Måns Magnusson, Jonathan H. Huggins, Aki Vehtari. [doi]
• Explicit Regularisation in Gaussian Noise InjectionsAlexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes. [doi]
• Online Non-Convex Optimization with Imperfect FeedbackAmélie Héliou, Matthieu Martin, Panayotis Mertikopoulos, Thibaud Rahier. [doi]
• ARMA Nets: Expanding Receptive Field for Dense PredictionJiahao Su, Shiqi Wang 0003, Furong Huang. [doi]
• CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent EstimationMakan Arastuie, Subhadeep Paul, Kevin S. Xu 0001. [doi]
• Meta-learning from Tasks with Heterogeneous Attribute SpacesTomoharu Iwata, Atsutoshi Kumagai. [doi]
• PAC-Bayes Learning Bounds for Sample-Dependent PriorsPranjal Awasthi, Satyen Kale, Stefani Karp, Mehryar Mohri. [doi]
• Training Normalizing Flows with the Information Bottleneck for Competitive Generative ClassificationLynton Ardizzone, Radek Mackowiak, Carsten Rother, Ullrich Köthe. [doi]
• Finite Continuum-Armed BanditsSolenne Gaucher. [doi]
• Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian ProcessesQuang Minh Hoang, Nghia Hoang, Hai Pham, David P. Woodruff. [doi]
• EvolveGraph: Multi-Agent Trajectory Prediction with Dynamic Relational ReasoningJiachen Li, Fan Yang, Masayoshi Tomizuka, Chiho Choi. [doi]
• Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network LearningRunzhong Wang, Junchi Yan, Xiaokang Yang. [doi]
• Adversarial Attacks on Deep Graph MatchingZijie Zhang, Zeru Zhang, Yang Zhou 0001, Yelong Shen, Ruoming Jin, Dejing Dou. [doi]
• On the Modularity of HypernetworksTomer Galanti, Lior Wolf. [doi]
• Universally Quantized Neural CompressionEirikur Agustsson, Lucas Theis. [doi]
• A Simple Language Model for Task-Oriented DialogueEhsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, Richard Socher. [doi]
• Learning Causal Effects via Weighted Empirical Risk MinimizationYonghan Jung, Jin Tian 0001, Elias Bareinboim. [doi]
• A Class of Algorithms for General Instrumental Variable ModelsNiki Kilbertus, Matt J. Kusner, Ricardo Silva. [doi]
• Compressing Images by Encoding Their Latent Representations with Relative Entropy CodingGergely Flamich, Marton Havasi, José Miguel Hernández-Lobato. [doi]
• PlanGAN: Model-based Planning With Sparse Rewards and Multiple GoalsHenry Charlesworth, Giovanni Montana. [doi]
• Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search SpacesHung Tran-The, Sunil Gupta 0001, Santu Rana, Huong Ha, Svetha Venkatesh. [doi]
• Optimization and Generalization Analysis of Transduction through Gradient Boosting and Application to Multi-scale Graph Neural NetworksKenta Oono, Taiji Suzuki. [doi]
• Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement LearningYounggyo Seo, Kimin Lee, Ignasi Clavera Gilaberte, Thanard Kurutach, Jinwoo Shin, Pieter Abbeel. [doi]
• Correspondence learning via linearly-invariant embeddingRiccardo Marin, Marie-Julie Rakotosaona, Simone Melzi, Maks Ovsjanikov. [doi]
• Worst-Case Analysis for Randomly Collected DataJustin Y. Chen, Gregory Valiant, Paul Valiant. [doi]
• Instance-optimality in differential privacy via approximate inverse sensitivity mechanismsHilal Asi, John C. Duchi. [doi]
• Improving Inference for Neural Image CompressionYibo Yang, Robert Bamler, Stephan Mandt. [doi]
• Winning the Lottery with Continuous SparsificationPedro Savarese, Hugo Silva, Michael Maire. [doi]
• Deep AutomodulatorsAri Heljakka, Yuxin Hou, Juho Kannala, Arno Solin. [doi]
• Neutralizing Self-Selection Bias in Sampling for SortitionBailey Flanigan, Paul Gölz, Anupam Gupta, Ariel D. Procaccia. [doi]
• Consequences of Misaligned AISimon Zhuang, Dylan Hadfield-Menell. [doi]
• Structured Convolutions for Efficient Neural Network DesignYash Bhalgat, Yizhe Zhang, Jamie Menjay Lin, Fatih Porikli. [doi]
• Meta-Gradient Reinforcement Learning with an Objective Discovered OnlineZhongwen Xu, Hado Philip van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver. [doi]
• Differentiable Causal Discovery from Interventional DataPhilippe Brouillard, Sébastien Lachapelle, Alexandre Lacoste, Simon Lacoste-Julien, Alexandre Drouin. [doi]
• CodeCMR: Cross-Modal Retrieval For Function-Level Binary Source Code MatchingZeping Yu, Wenxin Zheng, Jiaqi Wang, Qiyi Tang 0003, Sen Nie, Shi Wu. [doi]
• Escaping the Gravitational Pull of SoftmaxJincheng Mei, Chenjun Xiao, Bo Dai, Lihong Li 0001, Csaba Szepesvári, Dale Schuurmans. [doi]
• Analysis and Design of Thompson Sampling for Stochastic Partial MonitoringTaira Tsuchiya, Junya Honda, Masashi Sugiyama. [doi]
• Multifaceted Uncertainty Estimation for Label-Efficient Deep LearningWeishi Shi, Xujiang Zhao, Feng Chen 0001, Qi Yu 0001. [doi]
• Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical ModelJiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar. [doi]
• LoCo: Local Contrastive Representation LearningYuwen Xiong, Mengye Ren, Raquel Urtasun. [doi]
• R-learning in actor-critic model offers a biologically relevant mechanism for sequential decision-makingSergey Shuvaev, Sarah Starosta, Duda Kvitsiani, Ádám Kepecs, Alexei A. Koulakov. [doi]
• MultiON: Benchmarking Semantic Map Memory using Multi-Object NavigationSaim Wani, Shivansh Patel, Unnat Jain, Angel X. Chang, Manolis Savva. [doi]
• A Closer Look at the Training Strategy for Modern Meta-LearningJiaxin Chen, Xiao-Ming Wu, Yanke Li, Qimai Li, Li-Ming Zhan, Fu-Lai Chung. [doi]
• Unsupervised Sound Separation Using Mixture Invariant TrainingScott Wisdom, Efthymios Tzinis, Hakan Erdogan, Ron J. Weiss, Kevin W. Wilson, John R. Hershey. [doi]
• The Dilemma of TriHard Loss and an Element-Weighted TriHard Loss for Person Re-IdentificationYihao Lv, Youzhi Gu, Xinggao Liu. [doi]
• Hard Negative Mixing for Contrastive LearningYannis Kalantidis, Mert Bülent Sariyildiz, Noé Pion, Philippe Weinzaepfel, Diane Larlus. [doi]
• An Imitation from Observation Approach to Transfer Learning with Dynamics MismatchSiddharth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, Peter Stone. [doi]
• Generative 3D Part Assembly via Dynamic Graph LearningGuanqi Zhan, Qingnan Fan, Kaichun Mo, Lin Shao, Baoquan Chen, Leonidas J. Guibas, Hao Dong. [doi]
• Learning to solve TV regularised problems with unrolled algorithmsHamza Cherkaoui, Jeremias Sulam, Thomas Moreau. [doi]
• A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic ConstraintsOmid Sadeghi, Prasanna Sanjay Raut, Maryam Fazel. [doi]
• Self-Supervised Few-Shot Learning on Point CloudsCharu Sharma, Manohar Kaul. [doi]
• Improving Neural Network Training in Low Dimensional Random BasesFrithjof Gressmann, Zach Eaton-Rosen, Carlo Luschi. [doi]
• Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningPan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec. [doi]
• Learning Latent Space Energy-Based Prior ModelBo Pang, Tian Han 0001, Erik Nijkamp, Song Chun Zhu, Ying Nian Wu. [doi]
• Logarithmic Pruning is All You NeedLaurent Orseau, Marcus Hutter, Omar Rivasplata. [doi]
• Learning the Linear Quadratic Regulator from Nonlinear ObservationsZakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford 0001. [doi]
• Instance-wise Feature GroupingAria Masoomi, Chieh Wu, Tingting Zhao, Zifeng Wang, Peter J. Castaldi, Jennifer G. Dy. [doi]
• Learning to Select Best Forecast Tasks for Clinical Outcome PredictionYuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai. [doi]
• Expert-Supervised Reinforcement Learning for Offline Policy Learning and EvaluationAaron Sonabend W., Junwei Lu, Leo Anthony Celi, Tianxi Cai, Peter Szolovits. [doi]
• SoftFlow: Probabilistic Framework for Normalizing Flow on ManifoldsHyeongju Kim, Hyeonseung Lee, Woo Hyun Kang, Joun Yeop Lee, Nam Soo Kim. [doi]
• Contextual Reserve Price Optimization in Auctions via Mixed Integer ProgrammingJoey Huchette, Haihao Lu, Hossein Esfandiari, Vahab S. Mirrokni. [doi]
• Lamina-specific neuronal properties promote robust, stable signal propagation in feedforward networksDongqi Han, Erik De Schutter, Sungho Hong. [doi]
• Throughput-Optimal Topology Design for Cross-Silo Federated LearningOthmane Marfoq, Chuan Xu, Giovanni Neglia, Richard Vidal. [doi]
• The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement LearningHarm van Seijen, Hadi Nekoei, Evan Racah, Sarath Chandar. [doi]
• A Generalized Neural Tangent Kernel Analysis for Two-layer Neural NetworksZixiang Chen, Yuan Cao, Quanquan Gu, Tong Zhang 0001. [doi]
• Distributed Distillation for On-Device LearningIlai Bistritz, Ariana Mann, Nicholas Bambos. [doi]
• Lipschitz-Certifiable Training with a Tight Outer BoundSungyoon Lee, Jaewook Lee 0001, Saerom Park. [doi]
• Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased ExpectationsKevin Scaman, Cédric Malherbe. [doi]
• Causal Estimation with Functional ConfoundersAahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath. [doi]
• Continual Learning in Low-rank Orthogonal SubspacesArslan Chaudhry, Naeemullah Khan, Puneet K. Dokania, Philip H. S. Torr. [doi]
• Firefly Neural Architecture Descent: a General Approach for Growing Neural NetworksLemeng Wu, Bo Liu, Peter Stone, Qiang Liu 0001. [doi]
• Self-Learning Transformations for Improving Gaze and Head RedirectionYufeng Zheng, Seonwook Park, Xucong Zhang, Shalini De Mello, Otmar Hilliges. [doi]
• Adversarially Robust Streaming Algorithms via Differential PrivacyAvinatan Hassidim, Haim Kaplan, Yishay Mansour, Yossi Matias, Uri Stemmer. [doi]
• A Dictionary Approach to Domain-Invariant Learning in Deep NetworksZe Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu. [doi]
• Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign DropoutZhao Chen, Jiquan Ngiam, Yanping Huang, Thang Luong, Henrik Kretzschmar, Yuning Chai, Dragomir Anguelov. [doi]
• X-CAL: Explicit Calibration for Survival AnalysisMark Goldstein, Xintian Han, Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath. [doi]
• Improving Sparse Vector Technique with Renyi Differential PrivacyYuqing Zhu 0005, Yu-Xiang Wang. [doi]
• Quantitative Propagation of Chaos for SGD in Wide Neural NetworksValentin De Bortoli, Alain Durmus, Xavier Fontaine, Umut Simsekli. [doi]
• Impossibility Results for Grammar-Compressed Linear AlgebraAmir Abboud, Arturs Backurs, Karl Bringmann, Marvin Künnemann. [doi]
• A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning InstancesDieqiao Feng, Carla P. Gomes, Bart Selman. [doi]
• Stein Self-Repulsive Dynamics: Benefits From Past SamplesMao Ye, Tongzheng Ren, Qiang Liu 0001. [doi]
• A polynomial-time algorithm for learning nonparametric causal graphsMing Gao, Yi Ding 0006, Bryon Aragam. [doi]
• Finite-Sample Analysis of Contractive Stochastic Approximation Using Smooth Convex EnvelopesZaiwei Chen, Siva Theja Maguluri, Sanjay Shakkottai, Karthikeyan Shanmugam. [doi]
• The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic NoiseIlias Diakonikolas, Daniel M. Kane, Pasin Manurangsi. [doi]
• Towards practical differentially private causal graph discoveryLun Wang, Qi Pang, Dawn Song. [doi]
• Improved Sample Complexity for Incremental Autonomous Exploration in MDPsJean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric. [doi]
• Adaptive Probing Policies for Shortest Path RoutingAditya Bhaskara, Sreenivas Gollapudi, Kostas Kollias, Kamesh Munagala. [doi]
• Improving Local Identifiability in Probabilistic Box EmbeddingsShib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Li 0069, Andrew McCallum. [doi]
• Fair regression with Wasserstein barycentersEvgenii Chzhen, Christophe Denis, Mohamed Hebiri, Luca Oneto, Massimiliano Pontil. [doi]
• On Regret with Multiple Best ArmsYinglun Zhu, Robert Nowak 0001. [doi]
• Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution TestsSean Kulinski, Saurabh Bagchi, David I. Inouye. [doi]
• Learning Multi-Agent Communication through Structured Attentive ReasoningMurtaza Rangwala, Ryan Williams. [doi]
• A mathematical model for automatic differentiation in machine learningJérôme Bolte, Edouard Pauwels. [doi]
• Graph Geometry Interaction LearningShichao Zhu, Shirui Pan, Chuan Zhou 0001, Jia Wu 0001, Yanan Cao, Bin Wang 0004. [doi]
• A Ranking-based, Balanced Loss Function Unifying Classification and Localisation in Object DetectionKemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan. [doi]
• Efficient Clustering for Stretched Mixtures: Landscape and OptimalityKaizheng Wang, Yuling Yan, Mateo Díaz. [doi]
• Online Optimization with Memory and Competitive ControlGuanya Shi, Yiheng Lin, Soon Jo Chung, Yisong Yue, Adam Wierman. [doi]
• Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian RewardsVrettos Moulos. [doi]
• Adaptive Shrinkage Estimation for Streaming GraphsNesreen K. Ahmed, Nick Duffield. [doi]
• A Boolean Task Algebra for Reinforcement LearningGeraud Nangue Tasse, Steven James, Benjamin Rosman. [doi]
• Information Maximization for Few-Shot LearningMalik Boudiaf, Imtiaz Masud Ziko, Jérôme Rony, Jose Dolz, Pablo Piantanida, Ismail Ben Ayed. [doi]
• Robust Federated Learning: The Case of Affine Distribution ShiftsAmirhossein Reisizadeh, Farzan Farnia, Ramtin Pedarsani, Ali Jadbabaie. [doi]
• Detection as Regression: Certified Object Detection with Median SmoothingPing-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson 0001, Tom Goldstein. [doi]
• A Bayesian Perspective on Training Speed and Model SelectionClare Lyle, Lisa Schut, Robin Ru, Yarin Gal, Mark van der Wilk. [doi]
• Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic SystemsMayalen Etcheverry, Clément Moulin-Frier, Pierre-Yves Oudeyer. [doi]
• A Randomized Algorithm to Reduce the Support of Discrete MeasuresFrancesco Cosentino, Harald Oberhauser, Alessandro Abate. [doi]
• Task-Agnostic Amortized Inference of Gaussian Process HyperparametersSulin Liu, Xingyuan Sun, Peter J. Ramadge, Ryan P. Adams. [doi]
• COBE: Contextualized Object Embeddings from Narrated Instructional VideoGedas Bertasius, Lorenzo Torresani. [doi]
• Learning Graph Structure With A Finite-State Automaton LayerDaniel D. Johnson 0003, Hugo Larochelle, Daniel Tarlow. [doi]
• Searching for Low-Bit Weights in Quantized Neural NetworksZhaohui Yang, Yunhe Wang, Kai Han, Chunjing Xu, Chao Xu 0006, Dacheng Tao, Chang Xu 0002. [doi]
• Optimal Robustness-Consistency Trade-offs for Learning-Augmented Online AlgorithmsAlexander Wei, Fred Zhang. [doi]
• The All-or-Nothing Phenomenon in Sparse Tensor PCAJonathan Niles-Weed, Ilias Zadik. [doi]
• A mean-field analysis of two-player zero-sum gamesCarles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna. [doi]
• CrossTransformers: spatially-aware few-shot transferCarl Doersch, Ankush Gupta, Andrew Zisserman. [doi]
• Efficient estimation of neural tuning during naturalistic behaviorEdoardo Balzani, Kaushik J. Lakshminarasimhan, Dora E. Angelaki, Cristina Savin. [doi]
• Deterministic Approximation for Submodular Maximization over a Matroid in Nearly Linear TimeKai Han, Zongmai Cao, Shuang Cui, Benwei Wu. [doi]
• Can the Brain Do Backpropagation? - Exact Implementation of Backpropagation in Predictive Coding NetworksYuhang Song 0001, Thomas Lukasiewicz, Zhenghua Xu, Rafal Bogacz. [doi]
• Ratio Trace Formulation of Wasserstein Discriminant AnalysisHexuan Liu, Yunfeng Cai, You-Lin Chen, Ping Li 0001. [doi]
• Reinforced Molecular Optimization with Neighborhood-Controlled GrammarsChencheng Xu, Qiao Liu, Minlie Huang, Tao Jiang 0001. [doi]
• Group Contextual Encoding for 3D Point CloudsXu Liu, Chengtao Li, Jian Wang, Jingbo Wang, Boxin Shi, Xiaodong He. [doi]
• Interventional Few-Shot LearningZhongqi Yue, Hanwang Zhang, Qianru Sun, Xian-Sheng Hua 0001. [doi]
• Autoregressive Score MatchingChenlin Meng, Lantao Yu, Yang Song 0011, Jiaming Song, Stefano Ermon. [doi]
• Ensembling geophysical models with Bayesian Neural NetworksUshnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young. [doi]
• Principal Neighbourhood Aggregation for Graph NetsGabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Velickovic. [doi]
• Direct Policy Gradients: Direct Optimization of Policies in Discrete Action SpacesGuy Lorberbom, Chris J. Maddison, Nicolas Heess, Tamir Hazan, Daniel Tarlow. [doi]
• Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian MarginalsIlias Diakonikolas, Daniel Kane, Nikos Zarifis. [doi]
• Generative causal explanations of black-box classifiersMatthew R. O'Shaughnessy, Gregory Canal, Marissa Connor, Christopher Rozell, Mark A. Davenport. [doi]
• Gradient Estimation with Stochastic Softmax TricksMax B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause 0001, Chris J. Maddison. [doi]
• Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classificationFrancesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová. [doi]
• Neural Controlled Differential Equations for Irregular Time SeriesPatrick Kidger, James Morrill, James Foster, Terry J. Lyons. [doi]
• Linear Dynamical Systems as a Core Computational PrimitiveShiva Kaul. [doi]