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ORCIDJoelle Pineau
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- affiliation: McGill University, Montreal, Canada
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2020 – today
- 2024
[c154]Peter Henderson
, Jieru Hu, Mona T. Diab, Joelle Pineau:
Rethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct. CSLAW 2024: 109-120- [c153]Maxime Wabartha, Joelle Pineau:
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning. ICLR 2024 - [c152]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
Position: On the Societal Impact of Open Foundation Models. ICML 2024 - [i120]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
On the Societal Impact of Open Foundation Models. CoRR abs/2403.07918 (2024) - 2023
- [j39]Martin Cousineau, Vedat Verter, Susan A. Murphy, Joelle Pineau:
Estimating causal effects with optimization-based methods: A review and empirical comparison. Eur. J. Oper. Res. 304(2): 367-380 (2023) - [j38]Madhulika Srikumar, Rebecca Finlay, Grace Abuhamad, Carolyn Ashurst, Rosie Campbell, Emily Campbell-Ratcliffe, Hudson Hongo, Sara R. Jordan, Joseph Lindley, Aviv Ovadya, Joelle Pineau:
Publisher Correction: Advancing ethics review practices in AI research. Nat. Mac. Intell. 5(1): 94 (2023) - [j37]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. Trans. Assoc. Comput. Linguistics 11: 600-616 (2023) - [j36]Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau:
Group Fairness in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - 2022
- [j35]Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Varun Gupta, Iulian Vlad Serban, Joelle Pineau:
Automated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems. Int. J. Artif. Intell. Educ. 32(2): 323-349 (2022) - [j34]Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau:
Low-Rank Representation of Reinforcement Learning Policies. J. Artif. Intell. Res. 75: 597-636 (2022) - [j33]Madhulika Srikumar, Rebecca Finlay, Grace Abuhamad, Carolyn Ashurst, Rosie Campbell, Emily Campbell-Ratcliffe, Hudson Hongo, Sara R. Jordan, Joseph Lindley, Aviv Ovadya, Joelle Pineau:
Advancing ethics review practices in AI research. Nat. Mac. Intell. 4(12): 1061-1064 (2022) - [c151]Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau:
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions. AAAI 2022: 6829-6837 - [c150]Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer:
Improving Passage Retrieval with Zero-Shot Question Generation. EMNLP 2022: 3781-3797 - [c149]Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, Adina Williams:
The Curious Case of Absolute Position Embeddings. EMNLP (Findings) 2022: 4449-4472 - [c148]Lucas Caccia, Rahaf Aljundi, Nader Asadi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky:
New Insights on Reducing Abrupt Representation Change in Online Continual Learning. ICLR 2022 - [c147]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. ICML 2022: 24414-24429 - [c146]Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang:
Block Contextual MDPs for Continual Learning. L4DC 2022: 608-623 - [i119]Anthony GX-Chen, Veronica Chelu, Blake A. Richards, Joelle Pineau:
A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions. CoRR abs/2201.01836 (2022) - [i118]Annie Xie, Shagun Sodhani, Chelsea Finn, Joelle Pineau, Amy Zhang:
Robust Policy Learning over Multiple Uncertainty Sets. CoRR abs/2202.07013 (2022) - [i117]Thang Doan, Seyed-Iman Mirzadeh, Joelle Pineau, Mehrdad Farajtabar:
Efficient Continual Learning Ensembles in Neural Network Subspaces. CoRR abs/2202.09826 (2022) - [i116]Martin Cousineau, Vedat Verter, Susan A. Murphy, Joelle Pineau:
Estimating causal effects with optimization-based methods: A review and empirical comparison. CoRR abs/2203.00097 (2022) - [i115]Devendra Singh Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, Luke Zettlemoyer:
Improving Passage Retrieval with Zero-Shot Question Generation. CoRR abs/2204.07496 (2022) - [i114]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. CoRR abs/2206.10658 (2022) - [i113]Koustuv Sinha, Amirhossein Kazemnejad, Siva Reddy, Joelle Pineau, Dieuwke Hupkes, Adina Williams:
The Curious Case of Absolute Position Embeddings. CoRR abs/2210.12574 (2022) - 2021
- [j32]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program). J. Mach. Learn. Res. 22: 164:1-164:20 (2021) - [c145]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI 2021: 10674-10681 - [c144]Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, Adina Williams:
UnNatural Language Inference. ACL/IJCNLP (1) 2021: 7329-7346 - [c143]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning? AAMAS 2021: 1082-1090 - [c142]Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton:
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. EACL 2021: 2816-2822 - [c141]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. EMNLP (1) 2021: 2888-2913 - [c140]Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams:
Sometimes We Want Ungrammatical Translations. EMNLP (Findings) 2021: 3205-3227 - [c139]Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau:
Learning Robust State Abstractions for Hidden-Parameter Block MDPs. ICLR 2021 - [c138]Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau:
Regularized Inverse Reinforcement Learning. ICLR 2021 - [c137]Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim:
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. ICML 2021: 6120-6130 - [c136]Shagun Sodhani, Amy Zhang, Joelle Pineau:
Multi-Task Reinforcement Learning with Context-based Representations. ICML 2021: 9767-9779 - [c135]Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche:
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs. NeurIPS 2021: 2004-2017 - [c134]Prasanna Parthasarathi, Mohamed A. Abdelsalam, Sarath Chandar, Joelle Pineau:
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. SIGDIAL 2021: 469-476 - [c133]Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar:
Do Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task ? SIGDIAL 2021: 477-488 - [c132]Lucas Caccia, Joelle Pineau:
SPeCiaL: Self-supervised Pretraining for Continual Learning. CSSL 2021: 91-103 - [p1]Sylvie Delacroix, Joelle Pineau, Jessica Montgomery:
Democratising the Digital Revolution: The Role of Data Governance. Reflections on Artificial Intelligence for Humanity 2021: 40-52 - [i112]Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, Adina Williams:
Unnatural Language Inference. CoRR abs/2101.00010 (2021) - [i111]Anuroop Sriram, Matthew J. Muckley, Koustuv Sinha, Farah Shamout, Joelle Pineau, Krzysztof J. Geras, Lea Azour, Yindalon Aphinyanaphongs, Nafissa Yakubova, William Moore:
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction. CoRR abs/2101.04909 (2021) - [i110]Dora Jambor, Komal K. Teru, Joelle Pineau, William L. Hamilton:
Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs. CoRR abs/2102.03419 (2021) - [i109]Shagun Sodhani, Amy Zhang, Joelle Pineau:
Multi-Task Reinforcement Learning with Context-based Representations. CoRR abs/2102.06177 (2021) - [i108]Bonnie Li, Vincent François-Lavet, Thang Doan, Joelle Pineau:
Domain Adversarial Reinforcement Learning. CoRR abs/2102.07097 (2021) - [i107]Manan Tomar, Amy Zhang, Roberto Calandra, Matthew E. Taylor, Joelle Pineau:
Model-Invariant State Abstractions for Model-Based Reinforcement Learning. CoRR abs/2102.09850 (2021) - [i106]Kalesha Bullard, Douwe Kiela, Joelle Pineau, Jakob N. Foerster:
Quasi-Equivalence Discovery for Zero-Shot Emergent Communication. CoRR abs/2103.08067 (2021) - [i105]Lucas Caccia, Rahaf Aljundi, Tinne Tuytelaars, Joelle Pineau, Eugene Belilovsky:
Reducing Representation Drift in Online Continual Learning. CoRR abs/2104.05025 (2021) - [i104]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. CoRR abs/2104.06644 (2021) - [i103]Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams:
Sometimes We Want Translationese. CoRR abs/2104.07623 (2021) - [i102]Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche:
Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs. CoRR abs/2106.00099 (2021) - [i101]Emmanuel Bengio, Joelle Pineau, Doina Precup:
Correcting Momentum in Temporal Difference Learning. CoRR abs/2106.03955 (2021) - [i100]Lucas Caccia, Joelle Pineau:
SPeCiaL: Self-Supervised Pretraining for Continual Learning. CoRR abs/2106.09065 (2021) - [i99]Prasanna Parthasarathi, Mohamed A. Abdelsalam, Joelle Pineau, Sarath Chandar:
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss. CoRR abs/2106.10619 (2021) - [i98]Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar:
Do Encoder Representations of Generative Dialogue Models Encode Sufficient Information about the Task ? CoRR abs/2106.10622 (2021) - [i97]Jongmin Lee, Wonseok Jeon, Byung-Jun Lee, Joelle Pineau, Kee-Eung Kim:
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. CoRR abs/2106.10783 (2021) - [i96]Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang:
Block Contextual MDPs for Continual Learning. CoRR abs/2110.06972 (2021) - 2020
- [j31]Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio:
The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach. J. Artif. Intell. Res. 69: 571-612 (2020) - [j30]Nathan Peiffer-Smadja, Redwan Maatoug, François-Xavier Lescure, Eric D'ortenzio, Joelle Pineau, Jean-Rémi King:
Machine Learning for COVID-19 needs global collaboration and data-sharing. Nat. Mach. Intell. 2(6): 293-294 (2020) - [c131]Eric Crawford, Joelle Pineau:
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking. AAAI 2020: 3684-3692 - [c130]Qizhen Zhang, Audrey Durand, Joelle Pineau:
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract). AAAI 2020: 13983-13984 - [c129]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. ACL 2020: 2430-2441 - [c128]Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Varun Gupta, Iulian Vlad Serban, Joelle Pineau:
Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System. AIED (2) 2020: 140-146 - [c127]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED (2) 2020: 387-392 - [c126]Joelle Pineau:
Building reproducible, reusable, and robust machine learning software. DEBS 2020: 2 - [c125]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. ICLR 2020 - [c124]Ryan Lowe, Abhinav Gupta, Jakob N. Foerster, Douwe Kiela, Joelle Pineau:
On the interaction between supervision and self-play in emergent communication. ICLR 2020 - [c123]Emmanuel Bengio, Joelle Pineau, Doina Precup:
Interference and Generalization in Temporal Difference Learning. ICML 2020: 767-777 - [c122]Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau:
Online Learned Continual Compression with Adaptive Quantization Modules. ICML 2020: 1240-1250 - [c121]Harsh Satija, Philip Amortila, Joelle Pineau:
Constrained Markov Decision Processes via Backward Value Functions. ICML 2020: 8502-8511 - [c120]Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup:
Invariant Causal Prediction for Block MDPs. ICML 2020: 11214-11224 - [c119]Maxime Wabartha, Audrey Durand, Vincent François-Lavet, Joelle Pineau:
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI 2020: 2140-2147 - [c118]Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau:
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract). IJCAI 2020: 5055-5059 - [c117]Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra:
Plan2Vec: Unsupervised Representation Learning by Latent Plans. L4DC 2020: 935-946 - [c116]Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai:
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization. NeurIPS 2020 - [c115]Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau:
Novelty Search in Representational Space for Sample Efficient Exploration. NeurIPS 2020 - [c114]Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent:
Stable Policy Optimization via Off-Policy Divergence Regularization. UAI 2020: 1328-1337 - [i95]Ryan Lowe, Abhinav Gupta, Jakob N. Foerster, Douwe Kiela, Joelle Pineau:
On the interaction between supervision and self-play in emergent communication. CoRR abs/2002.01093 (2020) - [i94]Bogdan Mazoure, Thang Doan, Tianyu Li, Vladimir Makarenkov, Joelle Pineau, Doina Precup, Guillaume Rabusseau:
Provably efficient reconstruction of policy networks. CoRR abs/2002.02863 (2020) - [i93]Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau:
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. CoRR abs/2002.05651 (2020) - [i92]Wonseok Jeon, Paul Barde, Derek Nowrouzezahrai, Joelle Pineau:
Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic. CoRR abs/2002.10525 (2020) - [i91]Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent:
Stable Policy Optimization via Off-Policy Divergence Regularization. CoRR abs/2003.04108 (2020) - [i90]Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup:
Invariant Causal Prediction for Block MDPs. CoRR abs/2003.06016 (2020) - [i89]Emmanuel Bengio, Joelle Pineau, Doina Precup:
Interference and Generalization in Temporal Difference Learning. CoRR abs/2003.06350 (2020) - [i88]Koustuv Sinha, Shagun Sodhani, Joelle Pineau, William L. Hamilton:
Evaluating Logical Generalization in Graph Neural Networks. CoRR abs/2003.06560 (2020) - [i87]Joelle Pineau, Philippe Vincent-Lamarre, Koustuv Sinha, Vincent Larivière, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Hugo Larochelle:
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program). CoRR abs/2003.12206 (2020) - [i86]Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L. Hamilton, Joelle Pineau:
Learning an Unreferenced Metric for Online Dialogue Evaluation. CoRR abs/2005.00583 (2020) - [i85]Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Varun Gupta, Iulian Vlad Serban, Joelle Pineau:
Automated Personalized Feedback Improves Learning Gains in an Intelligent Tutoring System. CoRR abs/2005.02431 (2020) - [i84]Ge Yang, Amy Zhang, Ari S. Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra:
Plan2Vec: Unsupervised Representation Learning by Latent Plans. CoRR abs/2005.03648 (2020) - [i83]Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung Do Vu, Robert Belfer, Joelle Pineau, Aaron C. Courville, Laurent Charlin, Yoshua Bengio:
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. CoRR abs/2005.06616 (2020) - [i82]Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Christopher J. Pal, Derek Nowrouzezahrai:
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization. CoRR abs/2006.13258 (2020) - [i81]Deepak Sharma, Audrey Durand, Marc-André Legault, Louis-Philippe Lemieux Perreault, Audrey Lemaçon, Marie-Pierre Dubé, Joelle Pineau:
Deep interpretability for GWAS. CoRR abs/2007.01516 (2020) - [i80]Joshua Romoff, Peter Henderson, David Kanaa, Emmanuel Bengio, Ahmed Touati, Pierre-Luc Bacon, Joelle Pineau:
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning? CoRR abs/2007.02786 (2020) - [i79]Amy Zhang, Shagun Sodhani, Khimya Khetarpal, Joelle Pineau:
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP. CoRR abs/2007.07206 (2020) - [i78]Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar:
How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics. CoRR abs/2008.10427 (2020) - [i77]Harsh Satija, Philip Amortila, Joelle Pineau:
Constrained Markov Decision Processes via Backward Value Functions. CoRR abs/2008.11811 (2020) - [i76]Ruo Yu Tao, Vincent François-Lavet, Joelle Pineau:
Novelty Search in representational space for sample efficient exploration. CoRR abs/2009.13579 (2020) - [i75]Wonseok Jeon, Chen-Yang Su, Paul Barde, Thang Doan, Derek Nowrouzezahrai, Joelle Pineau:
Regularized Inverse Reinforcement Learning. CoRR abs/2010.03691 (2020) - [i74]Kalesha Bullard, Franziska Meier, Douwe Kiela, Joelle Pineau, Jakob N. Foerster:
Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations. CoRR abs/2010.15896 (2020) - [i73]Melissa Mozifian, Amy Zhang, Joelle Pineau, David Meger:
Intervention Design for Effective Sim2Real Transfer. CoRR abs/2012.02055 (2020)
2010 – 2019
- 2019
- [j29]Vincent François-Lavet, Guillaume Rabusseau, Joelle Pineau, Damien Ernst, Raphael Fonteneau:
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability. J. Artif. Intell. Res. 65: 1-30 (2019) - [c113]Eric Crawford, Joelle Pineau:
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks. AAAI 2019: 3412-3420 - [c112]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
On-Line Adaptative Curriculum Learning for GANs. AAAI 2019: 3470-3477 - [c111]Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau:
Combined Reinforcement Learning via Abstract Representations. AAAI 2019: 3582-3589 - [c110]Boyu Wang, Hejia Zhang, Peng Liu, Zebang Shen, Joelle Pineau:
Multitask Metric Learning: Theory and Algorithm. AISTATS 2019: 3362-3371 - [c109]Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin:
On the Pitfalls of Measuring Emergent Communication. AAMAS 2019: 693-701 - [c108]Bogdan Mazoure, Thang Doan, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRL 2019: 430-444 - [c107]Abhinav Gupta, Ryan Lowe, Jakob N. Foerster, Douwe Kiela, Joelle Pineau:
Seeded self-play for language learning. LANTERN@EMNLP-IJCNLP 2019: 62-66 - [c106]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. EMNLP/IJCNLP (1) 2019: 4505-4514 - [c105]Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, Joelle Pineau:
TarMAC: Targeted Multi-Agent Communication. ICML 2019: 1538-1546 - [c104]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill:
Separable value functions across time-scales. ICML 2019: 5468-5477 - [c103]Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau:
Deep Generative Modeling of LiDAR Data. IROS 2019: 5034-5040 - [c102]Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville:
No-Press Diplomacy: Modeling Multi-Agent Gameplay. NeurIPS 2019: 4476-4487 - [c101]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. NeurIPS 2019: 13299-13309 - [c100]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. UAI 2019: 422-432 - [i72]Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander H. Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, Shrimai Prabhumoye, Alan W. Black, Alexander I. Rudnicky, Jason D. Williams, Joelle Pineau, Mikhail Burtsev, Jason Weston:
The Second Conversational Intelligence Challenge (ConvAI2). CoRR abs/1902.00098 (2019) - [i71]Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau:
Separating value functions across time-scales. CoRR abs/1902.01883 (2019) - [i70]Ryan Lowe, Jakob N. Foerster, Y-Lan Boureau, Joelle Pineau, Yann N. Dauphin:
On the Pitfalls of Measuring Emergent Communication. CoRR abs/1903.05168 (2019) - [i69]Bogdan Mazoure, Thang Doan, Audrey Durand, R. Devon Hjelm, Joelle Pineau:
Leveraging exploration in off-policy algorithms via normalizing flows. CoRR abs/1905.06893 (2019) - [i68]Pierre Thodoroff, Nishanth Anand, Lucas Caccia, Doina Precup, Joelle Pineau:
Recurrent Value Functions. CoRR abs/1905.09562 (2019) - [i67]Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat:
Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. CoRR abs/1906.04585 (2019) - [i66]Amy Zhang, Zachary C. Lipton, Luis Pineda, Kamyar Azizzadenesheli, Anima Anandkumar, Laurent Itti, Joelle Pineau, Tommaso Furlanello:
Learning Causal State Representations of Partially Observable Environments. CoRR abs/1906.10437 (2019) - [i65]Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton:
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. CoRR abs/1908.06177 (2019) - [i64]Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron C. Courville:
No Press Diplomacy: Modeling Multi-Agent Gameplay. CoRR abs/1909.02128 (2019) - [i63]Thang Doan, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning. CoRR abs/1909.07543 (2019) - [i62]Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau:
Benchmarking Batch Deep Reinforcement Learning Algorithms. CoRR abs/1910.01708 (2019) - [i61]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. CoRR abs/1910.01741 (2019) - [i60]Viswanath Sivakumar, Tim Rocktäschel, Alexander H. Miller, Heinrich Küttler, Nantas Nardelli, Mike Rabbat, Joelle Pineau, Sebastian Riedel:
MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions. CoRR abs/1910.04054 (2019) - [i59]Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau:
Online Learned Continual Compression with Stacked Quantization Module. CoRR abs/1911.08019 (2019) - [i58]Eric Crawford, Joelle Pineau:
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking. CoRR abs/1911.09033 (2019) - 2018
- [j28]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version. Dialogue Discourse 9(1): 1-49 (2018) - [j27]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. 11(3-4): 219-354 (2018) - [j26]Mahmoud Ghorbel, Joelle Pineau, Richard Gourdeau, Shervin Javdani, Siddhartha S. Srinivasa:
A Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair. Int. J. Soc. Robotics 10(1): 131-145 (2018) - [j25]Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau:
Streaming kernel regression with provably adaptive mean, variance, and regularization. J. Mach. Learn. Res. 19: 17:1-17:34 (2018) - [c99]Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup:
OptionGAN: Learning Joint Reward-Policy Options Using Generative Adversarial Inverse Reinforcement Learning. AAAI 2018: 3199-3206 - [c98]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning That Matters. AAAI 2018: 3207-3214 - [c97]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. AIES 2018: 123-129 - [c96]Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRL 2018: 674-699 - [c95]Prasanna Parthasarathi, Joelle Pineau:
Extending Neural Generative Conversational Model using External Knowledge Sources. EMNLP 2018: 690-695 - [c94]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. ICLR (Workshop) 2018 - [c93]Amy Zhang, Harsh Satija, Joelle Pineau:
Decoupling Dynamics and Reward for Transfer Learning. ICLR (Workshop) 2018 - [c92]Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher J. Pal:
Focused Hierarchical RNNs for Conditional Sequence Processing. ICML 2018: 2559-2568 - [c91]Matthew J. A. Smith, Herke van Hoof, Joelle Pineau:
An Inference-Based Policy Gradient Method for Learning Options. ICML 2018: 4710-4719 - [c90]Audrey Durand, Charis Achilleos, Demetris Iacovides, Katerina Strati, Georgios D. Mitsis, Joelle Pineau:
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis. MLHC 2018: 67-82 - [c89]Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup:
Temporal Regularization for Markov Decision Process. NeurIPS 2018: 1784-1794 - [i57]Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Rajeswar, Alexandre de Brébisson, Jose M. R. Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio:
A Deep Reinforcement Learning Chatbot (Short Version). CoRR abs/1801.06700 (2018) - [i56]Valentin Thomas, Emmanuel Bengio, William Fedus, Jules Pondard, Philippe Beaudoin, Hugo Larochelle, Joelle Pineau, Doina Precup, Yoshua Bengio:
Disentangling the independently controllable factors of variation by interacting with the world. CoRR abs/1802.09484 (2018) - [i55]Amy Zhang, Harsh Satija, Joelle Pineau:
Decoupling Dynamics and Reward for Transfer Learning. CoRR abs/1804.10689 (2018) - [i54]Joshua Romoff, Alexandre Piché, Peter Henderson, Vincent François-Lavet, Joelle Pineau:
Reward Estimation for Variance Reduction in Deep Reinforcement Learning. CoRR abs/1805.03359 (2018) - [i53]Ahmed Touati, Harsh Satija, Joshua Romoff, Joelle Pineau, Pascal Vincent:
Randomized Value Functions via Multiplicative Normalizing Flows. CoRR abs/1806.02315 (2018) - [i52]Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Chris Pal:
Focused Hierarchical RNNs for Conditional Sequence Processing. CoRR abs/1806.04342 (2018) - [i51]Amy Zhang, Nicolas Ballas, Joelle Pineau:
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning. CoRR abs/1806.07937 (2018) - [i50]Iulian Vlad Serban, Chinnadhurai Sankar, Michael Pieper, Joelle Pineau, Yoshua Bengio:
The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach. CoRR abs/1807.04723 (2018) - [i49]Thang Doan, João Monteiro, Isabela Albuquerque, Bogdan Mazoure, Audrey Durand, Joelle Pineau, R. Devon Hjelm:
Online Adaptative Curriculum Learning for GANs. CoRR abs/1808.00020 (2018) - [i48]Vincent François-Lavet, Yoshua Bengio, Doina Precup, Joelle Pineau:
Combined Reinforcement Learning via Abstract Representations. CoRR abs/1809.04506 (2018) - [i47]Eric Crawford, Guillaume Rabusseau, Joelle Pineau:
Sequential Coordination of Deep Models for Learning Visual Arithmetic. CoRR abs/1809.04988 (2018) - [i46]Prasanna Parthasarathi, Joelle Pineau:
Extending Neural Generative Conversational Model using External Knowledge Sources. CoRR abs/1809.05524 (2018) - [i45]Peter Henderson, Joshua Romoff, Joelle Pineau:
Where Did My Optimum Go?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods. CoRR abs/1810.02525 (2018) - [i44]Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Michael G. Rabbat, Joelle Pineau:
TarMAC: Targeted Multi-Agent Communication. CoRR abs/1810.11187 (2018) - [i43]Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup:
Temporal Regularization in Markov Decision Process. CoRR abs/1811.00429 (2018) - [i42]Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau:
Adversarial Gain. CoRR abs/1811.01302 (2018) - [i41]Massimo Caccia, Lucas Caccia, William Fedus, Hugo Larochelle, Joelle Pineau, Laurent Charlin:
Language GANs Falling Short. CoRR abs/1811.02549 (2018) - [i40]Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban, Michael Noseworthy, Prasanna Parthasarathi, Joelle Pineau:
The RLLChatbot: a solution to the ConvAI challenge. CoRR abs/1811.02714 (2018) - [i39]Koustuv Sinha, Shagun Sodhani, William L. Hamilton, Joelle Pineau:
Compositional Language Understanding with Text-based Relational Reasoning. CoRR abs/1811.02959 (2018) - [i38]Amy Zhang, Yuxin Wu, Joelle Pineau:
Natural Environment Benchmarks for Reinforcement Learning. CoRR abs/1811.06032 (2018) - [i37]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. CoRR abs/1811.12560 (2018) - [i36]Lucas Caccia, Herke van Hoof, Aaron C. Courville, Joelle Pineau:
Deep Generative Modeling of LiDAR Data. CoRR abs/1812.01180 (2018) - 2017
- [j24]Ryan Thomas Lowe, Nissan Pow, Iulian Vlad Serban, Laurent Charlin, Chia-Wei Liu, Joelle Pineau:
Training End-to-End Dialogue Systems with the Ubuntu Dialogue Corpus. Dialogue Discourse 8(1): 31-65 (2017) - [j23]Ali Emami, Joseph El Youssef, Remi Rabasa-Lhoret, Joelle Pineau, Jessica R. Castle, Ahmad Haidar:
Modeling Glucagon Action in Patients With Type 1 Diabetes. IEEE J. Biomed. Health Informatics 21(4): 1163-1171 (2017) - [c88]Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio:
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. AAAI 2017: 3295-3301 - [c87]Ryan Lowe, Michael Noseworthy, Iulian Vlad Serban, Nicolas Angelard-Gontier, Yoshua Bengio, Joelle Pineau:
Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses. ACL (1) 2017: 1116-1126 - [c86]Matthew Smith, Laurent Charlin, Joelle Pineau:
A Sparse Probabilistic Model of User Preference Data. Canadian AI 2017: 316-328 - [c85]Iulian Vlad Serban, Alexander Ororbia, Joelle Pineau, Aaron C. Courville:
Piecewise Latent Variables for Neural Variational Text Processing. SPNLP@EMNLP 2017: 52-62 - [c84]Iulian Vlad Serban, Alexander G. Ororbia II, Joelle Pineau, Aaron C. Courville:
Piecewise Latent Variables for Neural Variational Text Processing. EMNLP 2017: 422-432 - [c83]Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio:
An Actor-Critic Algorithm for Sequence Prediction. ICLR (Poster) 2017 - [c82]Ryan Lowe, Michael Noseworthy, Iulian Vlad Serban, Nicolas Angelard-Gontier, Yoshua Bengio, Joelle Pineau:
Towards an automatic Turing test: Learning to evaluate dialogue responses. ICLR (Workshop) 2017 - [c81]Guillaume Rabusseau, Borja Balle, Joelle Pineau:
Multitask Spectral Learning of Weighted Automata. NIPS 2017: 2588-2597 - [c80]Hoai Phuoc Truong, Prasanna Parthasarathi, Joelle Pineau:
MACA: A Modular Architecture for Conversational Agents. SIGDIAL Conference 2017: 93-102 - [c79]Michael Noseworthy, Jackie Chi Kit Cheung, Joelle Pineau:
Predicting Success in Goal-Driven Human-Human Dialogues. SIGDIAL Conference 2017: 253-262 - [i35]Emmanuel Bengio, Valentin Thomas, Joelle Pineau, Doina Precup, Yoshua Bengio:
Independently Controllable Features. CoRR abs/1703.07718 (2017) - [i34]Audrey Durand, Odalric-Ambrym Maillard, Joelle Pineau:
Streaming kernel regression with provably adaptive mean, variance, and regularization. CoRR abs/1708.00768 (2017) - [i33]Valentin Thomas, Jules Pondard, Emmanuel Bengio, Marc Sarfati, Philippe Beaudoin, Marie-Jean Meurs, Joelle Pineau, Doina Precup, Yoshua Bengio:
Independently Controllable Factors. CoRR abs/1708.01289 (2017) - [i32]Ryan Lowe, Michael Noseworthy, Iulian Vlad Serban, Nicolas Angelard-Gontier, Yoshua Bengio, Joelle Pineau:
Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses. CoRR abs/1708.07149 (2017) - [i31]Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Mudumba, Alexandre de Brébisson, Jose Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio:
A Deep Reinforcement Learning Chatbot. CoRR abs/1709.02349 (2017) - [i30]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning that Matters. CoRR abs/1709.06560 (2017) - [i29]Peter Henderson, Wei-Di Chang, Pierre-Luc Bacon, David Meger, Joelle Pineau, Doina Precup:
OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning. CoRR abs/1709.06683 (2017) - [i28]Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R. Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio:
ACtuAL: Actor-Critic Under Adversarial Learning. CoRR abs/1711.04755 (2017) - [i27]Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau:
Ethical Challenges in Data-Driven Dialogue Systems. CoRR abs/1711.09050 (2017) - [i26]Xingwei Cao, Guillaume Rabusseau, Joelle Pineau:
Tensor Regression Networks with various Low-Rank Tensor Approximations. CoRR abs/1712.09520 (2017) - 2016
- [j22]Beomjoon Kim, Joelle Pineau:
Socially Adaptive Path Planning in Human Environments Using Inverse Reinforcement Learning. Int. J. Soc. Robotics 8(1): 51-66 (2016) - [j21]André da Motta Salles Barreto, Doina Precup, Joelle Pineau:
Practical Kernel-Based Reinforcement Learning. J. Mach. Learn. Res. 17: 67:1-67:70 (2016) - [j20]Boyu Wang, Joelle Pineau:
Online Bagging and Boosting for Imbalanced Data Streams. IEEE Trans. Knowl. Data Eng. 28(12): 3353-3366 (2016) - [c78]André da Motta Salles Barreto, Rafael L. Beirigo, Joelle Pineau, Doina Precup:
Incremental Stochastic Factorization for Online Reinforcement Learning. AAAI 2016: 1468-1475 - [c77]Boyu Wang, Joelle Pineau, Borja Balle:
Multitask Generalized Eigenvalue Program. AAAI 2016: 2115-2121 - [c76]Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, Joelle Pineau:
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models. AAAI 2016: 3776-3784 - [c75]Martin Gerdzhev, Joelle Pineau, Ian M. Mitchell, Pooja Viswanathan, Geneviève Foley:
On the Use of Modular Software and Hardware for Designing Wheelchair Robots. AAAI Spring Symposia 2016 - [c74]Chia-Wei Liu, Ryan Lowe, Iulian Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau:
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. EMNLP 2016: 2122-2132 - [c73]Chenghui Zhou, Borja Balle, Joelle Pineau:
Learning time series models for pedestrian motion prediction. ICRA 2016: 3323-3330 - [c72]Boyu Wang, Joelle Pineau:
Generalized Dictionary for Multitask Learning with Boosting. IJCAI 2016: 2097-2103 - [c71]Pierre Thodoroff, Joelle Pineau, Andrew Lim:
Learning Robust Features using Deep Learning for Automatic Seizure Detection. MLHC 2016: 178-190 - [c70]Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau:
On the Evaluation of Dialogue Systems with Next Utterance Classification. SIGDIAL Conference 2016: 264-269 - [i25]Chia-Wei Liu, Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau:
How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. CoRR abs/1603.08023 (2016) - [i24]Ryan Lowe, Iulian Vlad Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau:
On the Evaluation of Dialogue Systems with Next Utterance Classification. CoRR abs/1605.05414 (2016) - [i23]Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, Yoshua Bengio:
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues. CoRR abs/1605.06069 (2016) - [i22]Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio:
An Actor-Critic Algorithm for Sequence Prediction. CoRR abs/1607.07086 (2016) - [i21]Pierre Thodoroff, Joelle Pineau, Andrew Lim:
Learning Robust Features using Deep Learning for Automatic Seizure Detection. CoRR abs/1608.00220 (2016) - [i20]Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar:
Bayesian Reinforcement Learning: A Survey. CoRR abs/1609.04436 (2016) - [i19]Iulian Vlad Serban, Ryan Lowe, Laurent Charlin, Joelle Pineau:
Generative Deep Neural Networks for Dialogue: A Short Review. CoRR abs/1611.06216 (2016) - [i18]Iulian Vlad Serban, Alexander G. Ororbia II, Joelle Pineau, Aaron C. Courville:
Multi-modal Variational Encoder-Decoders. CoRR abs/1612.00377 (2016) - 2015
- [j19]Mohammad Ghavamzadeh, Shie Mannor, Joelle Pineau, Aviv Tamar:
Bayesian Reinforcement Learning: A Survey. Found. Trends Mach. Learn. 8(5-6): 359-483 (2015) - [c69]Boyu Wang, Joelle Pineau:
Online Boosting Algorithms for Anytime Transfer and Multitask Learning. AAAI 2015: 3038-3044 - [c68]Hang Ma, Joelle Pineau:
Information Gathering and Reward Exploitation of Subgoals for POMDPs. AAAI 2015: 3320-3326 - [c67]Audrey Durand, Joelle Pineau:
Adaptive Treatment Allocation Using Sub-Sampled Gaussian Processes. AAAI Fall Symposia 2015: 9-11 - [c66]Andrew Sutcliffe, Neil A. Tenenholtz, Joelle Pineau:
Missteps in Robot Social Navigation. AAAI Fall Symposia 2015: 134-136 - [c65]Joelle Pineau:
Improving the Design and Discovery of Dynamic Treatment Strategies Using Recent Results in Sequential Decision-Making. ICAPS 2015: 373- - [c64]Joelle Pineau, Pierre-Luc Bacon:
Analyzing Open Data from the City of Montreal. MUD@ICML 2015: 11-16 - [c63]Angus Leigh, Joelle Pineau, Nicolas A. Olmedo, Hong Zhang:
Person tracking and following with 2D laser scanners. ICRA 2015: 726-733 - [c62]André da Motta Salles Barreto, Rafael L. Beirigo, Joelle Pineau, Doina Precup:
An Expectation-Maximization Algorithm to Compute a Stochastic Factorization From Data. IJCAI 2015: 3329-3336 - [c61]HiuKim Yuen, Joelle Pineau, Philippe S. Archambault:
Automatically characterizing driving activities onboard smart wheelchairs from accelerometer data. IROS 2015: 5011-5018 - [c60]Ryan Lowe, Nissan Pow, Iulian Serban, Joelle Pineau:
The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems. SIGDIAL Conference 2015: 285-294 - [i17]Ryan Lowe, Nissan Pow, Iulian Serban, Joelle Pineau:
The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems. CoRR abs/1506.08909 (2015) - [i16]Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C. Courville, Joelle Pineau:
Hierarchical Neural Network Generative Models for Movie Dialogues. CoRR abs/1507.04808 (2015) - [i15]Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau, Doina Precup:
Conditional Computation in Neural Networks for faster models. CoRR abs/1511.06297 (2015) - [i14]Iulian Vlad Serban, Ryan Lowe, Peter Henderson, Laurent Charlin, Joelle Pineau:
A Survey of Available Corpora for Building Data-Driven Dialogue Systems. CoRR abs/1512.05742 (2015) - 2014
- [j18]André da Motta Salles Barreto, Joelle Pineau, Doina Precup:
Policy Iteration Based on Stochastic Factorization. J. Artif. Intell. Res. 50: 763-803 (2014) - [j17]William L. Hamilton, Mahdi Milani Fard, Joelle Pineau:
Efficient learning and planning with compressed predictive states. J. Mach. Learn. Res. 15(1): 3395-3439 (2014) - [c59]Andrew Sutcliffe, Daniel H. Grollman, Joelle Pineau:
Estimating People's Subjective Experiences of Robot Behavior. AAAI Fall Symposia 2014 - [c58]Borja Balle, William L. Hamilton, Joelle Pineau:
Methods of Moments for Learning Stochastic Languages: Unified Presentation and Empirical Comparison. ICML 2014: 1386-1394 - [c57]Ouais Alsharif, Joelle Pineau:
End-to-End Text Recognition with Hybrid HMM Maxout Models. ICLR (Workshop) 2014 - [i13]Stéphane Ross, Joelle Pineau, Sébastien Paquet, Brahim Chaib-draa:
Online Planning Algorithms for POMDPs. CoRR abs/1401.3436 (2014) - [i12]Mahdi Milani Fard, Joelle Pineau:
Non-Deterministic Policies in Markovian Decision Processes. CoRR abs/1401.3871 (2014) - [i11]Ouais Alsharif, Philip Bachman, Joelle Pineau:
Lifelong Learning of Discriminative Representations. CoRR abs/1404.4108 (2014) - [i10]André da Motta Salles Barreto, Doina Precup, Joelle Pineau:
Practical Kernel-Based Reinforcement Learning. CoRR abs/1407.5358 (2014) - 2013
- [j16]Guy Shani, Joelle Pineau, Robert Kaplow:
A survey of point-based POMDP solvers. Auton. Agents Multi Agent Syst. 27(1): 1-51 (2013) - [j15]Jordan Frank, Shie Mannor, Joelle Pineau, Doina Precup:
Time Series Analysis Using Geometric Template Matching. IEEE Trans. Pattern Anal. Mach. Intell. 35(3): 740-754 (2013) - [c56]Sylvie C. W. Ong, Yuri Grinberg, Joelle Pineau:
Mixed Observability Predictive State Representations. AAAI 2013: 746-752 - [c55]Joelle Pineau:
Designing Intelligent Wheelchairs: Reintegrating AI. AAAI Spring Symposium: Designing Intelligent Robots 2013 - [c54]William L. Hamilton, Mahdi Milani Fard, Joelle Pineau:
Modelling Sparse Dynamical Systems with Compressed Predictive State Representations. ICML (1) 2013: 178-186 - [c53]Beomjoon Kim, Amir-massoud Farahmand, Joelle Pineau, Doina Precup:
Learning from Limited Demonstrations. NIPS 2013: 2859-2867 - [c52]Mahdi Milani Fard, Yuri Grinberg, Amir-massoud Farahmand, Joelle Pineau, Doina Precup:
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces. NIPS 2013: 3030-3038 - [c51]Beomjoon Kim, Joelle Pineau:
Maximum Mean Discrepancy Imitation Learning. Robotics: Science and Systems 2013 - [i9]Boyu Wang, Joelle Pineau:
Online Ensemble Learning for Imbalanced Data Streams. CoRR abs/1310.8004 (2013) - [i8]William L. Hamilton, Mahdi Milani Fard, Joelle Pineau:
Efficient Learning and Planning with Compressed Predictive States. CoRR abs/1312.0286 (2013) - 2012
- [j14]Finale Doshi-Velez, Joelle Pineau, Nicholas Roy:
Reinforcement learning with limited reinforcement: Using Bayes risk for active learning in POMDPs. Artif. Intell. 187: 115-132 (2012) - [j13]ShaoWei Png, Joelle Pineau, Brahim Chaib-draa:
Building Adaptive Dialogue Systems Via Bayes-Adaptive POMDPs. IEEE J. Sel. Top. Signal Process. 6(8): 917-927 (2012) - [c50]Mahdi Milani Fard, Yuri Grinberg, Joelle Pineau, Doina Precup:
Compressed Least-Squares Regression on Sparse Spaces. AAAI 2012: 1054-1060 - [c49]Emily Tsang, Sylvie C. W. Ong, Joelle Pineau:
Design and Evaluation of a Flexible Interface for Spatial Navigation. CRV 2012: 353-360 - [c48]Cosmin Paduraru, Doina Precup, Joelle Pineau, Gheorghe Comanici:
An Empirical Analysis of Off-policy Learning in Discrete MDPs. EWRL 2012: 89-102 - [c47]André da Motta Salles Barreto, Doina Precup, Joelle Pineau:
On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization. NIPS 2012: 1493-1501 - [i7]Kun Deng, Joelle Pineau, Susan A. Murphy:
Active Learning for Developing Personalized Treatment. CoRR abs/1202.3714 (2012) - [i6]Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári:
PAC-Bayesian Policy Evaluation for Reinforcement Learning. CoRR abs/1202.3717 (2012) - [i5]Stéphane Ross, Joelle Pineau:
Model-Based Bayesian Reinforcement Learning in Large Structured Domains. CoRR abs/1206.3281 (2012) - [i4]John Langford, Joelle Pineau:
Proceedings of the 29th International Conference on Machine Learning (ICML-12). CoRR abs/1207.4676 (2012) - [i3]Mahdi Milani Fard, Yuri Grinberg, Amir Massoud Farahmand, Joelle Pineau, Doina Precup:
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces. CoRR abs/1207.5554 (2012) - [i2]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Policy-contingent abstraction for robust robot control. CoRR abs/1212.2495 (2012) - 2011
- [j12]Mahdi Milani Fard, Joelle Pineau:
Non-Deterministic Policies in Markovian Decision Processes. J. Artif. Intell. Res. 40: 1-24 (2011) - [j11]Stéphane Ross, Joelle Pineau, Brahim Chaib-draa, Pierre Kreitmann:
A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes. J. Mach. Learn. Res. 12: 1729-1770 (2011) - [j10]Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte, T. Scott Stroup, Joelle Pineau, Susan A. Murphy:
Informing sequential clinical decision-making through reinforcement learning: an empirical study. Mach. Learn. 84(1-2): 109-136 (2011) - [j9]Robert D. Vincent, Aaron C. Courville, Joelle Pineau:
A bistable computational model of recurring epileptiform activity as observed in rodent slice preparations. Neural Networks 24(6): 526-537 (2011) - [c46]Guillaume Saulnier, Joelle Pineau:
Automatic Seizure Detection in an In-Vivo Model of Epilepsy. AAAI Spring Symposium: Computational Physiology 2011 - [c45]Kun Deng, Joelle Pineau, Susan A. Murphy:
Active learning for personalizing treatment. ADPRL 2011: 32-39 - [c44]Athena K. Moghaddam, Joelle Pineau, Jordan Frank, Philippe S. Archambault, François Routhier, Therese Audet, Jan Polgar, François Michaud, Patrick Boissy:
Mobility profile and wheelchair driving skills of powered wheelchair users: Sensor-based event recognition using a support vector machine classifier. EMBC 2011: 7336-7339 - [c43]Sylvie C. W. Ong, Yuri Grinberg, Joelle Pineau:
Goal-Directed Online Learning of Predictive Models. EWRL 2011: 18-29 - [c42]Cosmin Paduraru, Doina Precup, Joelle Pineau:
A Framework for Computing Bounds for the Return of a Policy. EWRL 2011: 201-212 - [c41]ShaoWei Png, Joelle Pineau:
Bayesian reinforcement learning for POMDP-based dialogue systems. ICASSP 2011: 2156-2159 - [c40]André da Motta Salles Barreto, Doina Precup, Joelle Pineau:
Reinforcement Learning using Kernel-Based Stochastic Factorization. NIPS 2011: 720-728 - [c39]Monica Dinculescu, Christopher Hundt, Prakash Panangaden, Joelle Pineau, Doina Precup:
The Duality of State and Observation in Probabilistic Transition Systems. TbiLLC 2011: 206-230 - [c38]Kun Deng, Joelle Pineau, Susan A. Murphy:
Active Learning for Developing Personalized Treatment. UAI 2011: 161-168 - [c37]Mahdi Milani Fard, Joelle Pineau, Csaba Szepesvári:
PAC-Bayesian Policy Evaluation for Reinforcement Learning. UAI 2011: 195-202 - [i1]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Anytime Point-Based Approximations for Large POMDPs. CoRR abs/1110.0027 (2011) - 2010
- [c36]Keith Bush, Joelle Pineau:
Treating Epilepsy by Reinforcement Learning Via Manifold-Based Simulation. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - [c35]Robert West, Doina Precup, Joelle Pineau:
Automatically suggesting topics for augmenting text documents. CIKM 2010: 929-938 - [c34]Robert Kaplow, Amin Atrash, Joelle Pineau:
Variable resolution decomposition for robotic navigation under a POMDP framework. ICRA 2010: 369-376 - [c33]Arthur Guez, Joelle Pineau:
Multi-tasking SLAM. ICRA 2010: 377-384 - [c32]Mahdi Milani Fard, Joelle Pineau:
PAC-Bayesian Model Selection for Reinforcement Learning. NIPS 2010: 1624-1632 - [c31]Joelle Pineau, Robert West, Amin Atrash, Julien Villemure, François Routhier:
Towards a standardized test for intelligent wheelchairs. PerMIS 2010: 169-174
2000 – 2009
- 2009
- [j8]Razvan C. Bunescu, Vitor R. Carvalho, Jan Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H. Göker, Hans W. Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker, Wolfgang Ketter, Alfred Kobsa, Sven Koenig, Tessa A. Lau, Lundy Lewis, Eric T. Matson, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Joelle Pineau, Pascal Poupart, Anita Raja, Wheeler Ruml, Norman M. Sadeh, Guy Shani, Daniel G. Shapiro, Sarabjot Singh Anand, Matthew E. Taylor, Kiri Wagstaff, Trey Smith, William E. Walsh, Rong Zhou:
AAAI 2008 Workshop Reports. AI Mag. 30(1): 108-118 (2009) - [j7]Joelle Pineau, Arthur Guez, Robert D. Vincent, Gabriella Panuccio, Massimo Avoli:
Treating Epilepsy via Adaptive Neurostimulation: a Reinforcement Learning Approach. Int. J. Neural Syst. 19(4): 227-240 (2009) - [j6]Amin Atrash, Robert Kaplow, Julien Villemure, Robert West, Hiba Yamani, Joelle Pineau:
Development and Validation of a Robust Speech Interface for Improved Human-Robot Interaction. Int. J. Soc. Robotics 1(4): 345-356 (2009) - [c30]Robert West, Doina Precup, Joelle Pineau:
Completing wikipedia's hyperlink structure through dimensionality reduction. CIKM 2009: 1097-1106 - [c29]Robert West, Joelle Pineau, Doina Precup:
Wikispeedia: An Online Game for Inferring Semantic Distances between Concepts. IJCAI 2009: 1598-1603 - [c28]Amin Atrash, Joelle Pineau:
A bayesian reinforcement learning approach for customizing human-robot interfaces. IUI 2009: 355-360 - [c27]Keith Bush, Joelle Pineau:
Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability. NIPS 2009: 189-197 - 2008
- [j5]Stéphane Ross, Joelle Pineau, Sébastien Paquet, Brahim Chaib-draa:
Online Planning Algorithms for POMDPs. J. Artif. Intell. Res. 32: 663-704 (2008) - [c26]Mahdi Milani Fard, Joelle Pineau, Peng Sun:
A Variance Analysis for POMDP Policy Evaluation. AAAI 2008: 1056-1061 - [c25]Arthur Guez, Robert D. Vincent, Massimo Avoli, Joelle Pineau:
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning. AAAI 2008: 1671-1678 - [c24]Finale Doshi, Joelle Pineau, Nicholas Roy:
Reinforcement learning with limited reinforcement: using Bayes risk for active learning in POMDPs. ICML 2008: 256-263 - [c23]Stéphane Ross, Brahim Chaib-draa, Joelle Pineau:
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation. ICRA 2008: 2845-2851 - [c22]Finale Doshi, Joelle Pineau, Nicholas Roy:
Reinforcement Learning with Limited Reinforcement: Using Bayes Risk for Active Learning in POMDPs. ISAIM 2008 - [c21]Joelle Pineau, Stéphane Ross, Brahim Chaib-draa:
Bayes-Adaptive POMDPs: A New Perspective on the Explore-Exploit Tradeoff in Partially Observable Domains. ISAIM 2008 - [c20]Mahdi Milani Fard, Joelle Pineau:
MDPs with Non-Deterministic Policies. NIPS 2008: 1065-1072 - [c19]Stéphane Ross, Joelle Pineau:
Model-Based Bayesian Reinforcement Learning in Large Structured Domains. UAI 2008: 476-483 - 2007
- [j4]Robin Jaulmes, Joelle Pineau, Doina Precup:
Apprentissage actif dans les processus décisionnels de Markov partiellement observables L'algorithme MEDUSA. Rev. d'Intelligence Artif. 21(1): 9-34 (2007) - [c18]Christopher Hundt, Prakash Panangaden, Joelle Pineau, Doina Precup:
Representing Systems with Hidden State. AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development 2007: 17-23 - [c17]Joelle Pineau, Amin Atrash:
SmartWheeler: A Robotic Wheelchair Test-Bed for Investigating New Models of Human-Robot Interaction. AAAI Spring Symposium: Multidisciplinary Collaboration for Socially Assistive Robotics 2007: 59-64 - [c16]Robert D. Vincent, Joelle Pineau, Philip de Guzman, Massimo Avoli:
Recurrent Boosting for Classification of Natural and Synthetic Time-Series Data. Canadian AI 2007: 192-203 - [c15]Robin Jaulmes, Joelle Pineau, Doina Precup:
A formal framework for robot learning and control under model uncertainty. ICRA 2007: 2104-2110 - [c14]Stéphane Ross, Brahim Chaib-draa, Joelle Pineau:
Bayes-Adaptive POMDPs. NIPS 2007: 1225-1232 - [c13]Stéphane Ross, Joelle Pineau, Brahim Chaib-draa:
Theoretical Analysis of Heuristic Search Methods for Online POMDPs. NIPS 2007: 1233-1240 - 2006
- [j3]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Anytime Point-Based Approximations for Large POMDPs. J. Artif. Intell. Res. 27: 335-380 (2006) - [j2]Nikos Vlassis, Geoffrey J. Gordon, Joelle Pineau:
Planning under uncertainty in robotics. Robotics Auton. Syst. 54(11): 885-886 (2006) - [c12]Christopher Hundt, Prakash Panangaden, Joelle Pineau, Doina Precup:
Representing Systems with Hidden State. AAAI 2006: 368-374 - [c11]Daniel Burfoot, Joelle Pineau, Gregory Dudek:
RRT-Plan: A Randomized Algorithm for STRIPS Planning. ICAPS 2006: 362-365 - [c10]Ricard Gavaldà, Philipp W. Keller, Joelle Pineau, Doina Precup:
PAC-Learning of Markov Models with Hidden State. ECML 2006: 150-161 - 2005
- [c9]Robin Jaulmes, Joelle Pineau, Doina Precup:
Active Learning in Partially Observable Markov Decision Processes. ECML 2005: 601-608 - [c8]Joelle Pineau, Geoffrey J. Gordon:
POMDP Planning for Robust Robot Control. ISRR 2005: 69-82 - 2003
- [j1]Joelle Pineau, Michael Montemerlo, Martha E. Pollack, Nicholas Roy, Sebastian Thrun:
Towards robotic assistants in nursing homes: Challenges and results. Robotics Auton. Syst. 42(3-4): 271-281 (2003) - [c7]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Point-based value iteration: An anytime algorithm for POMDPs. IJCAI 2003: 1025-1032 - [c6]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Applying Metric-Trees to Belief-Point POMDPs. NIPS 2003: 759-766 - [c5]Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun:
Policy-contingent abstraction for robust robot control. UAI 2003: 477-484 - 2002
- [c4]Michael Montemerlo, Joelle Pineau, Nicholas Roy, Sebastian Thrun, Vandi Verma:
Experiences with a Mobile Robotic Guide for the Elderly. AAAI/IAAI 2002: 587-592 - [c3]Judith T. Matthews, Sandra Engberg, Michael Montemerlo, Joelle Pineau, Nicholas Roy, Joan Rogers, Sebastian Thrun:
Robotic Assistance During Ambulation by Older Adults. AMIA 2002 - 2000
- [c2]Nicholas Roy, Joelle Pineau, Sebastian Thrun:
Spoken Dialogue Management Using Probabilistic Reasoning. ACL 2000: 93-100 - [c1]David Goddeau, Joelle Pineau:
Fast reinforcement learning of dialog strategies. ICASSP 2000: 1233-1236
Coauthor Index
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