Table of Contents

• Incremental Local Evolutionary Outlier Detection for Dynamic Social NetworksTengfei Ji, Dongqing Yang, Jun Gao. 1-15 [doi]
• How Long Will She Call Me? Distribution, Social Theory and Duration PredictionYuxiao Dong, Jie Tang, Tiancheng Lou, Bin Wu, Nitesh V. Chawla. 16-31 [doi]
• Discovering Nested CommunitiesNikolaj Tatti, Aristides Gionis. 32-47 [doi]
• CSI: Community-Level Social Influence AnalysisYasir Mehmood, Nicola Barbieri, Francesco Bonchi, Antti Ukkonen. 48-63 [doi]
• Supervised Learning of Syntactic Contexts for Uncovering Definitions and Extracting Hypernym Relations in Text DatabasesGuido Boella, Luigi Di Caro. 64-79 [doi]
• Error Prediction with Partial FeedbackWilliam Darling, Cédric Archambeau, Shachar Mirkin, Guillaume Bouchard. 80-94 [doi]
• Boot-Strapping Language Identifiers for Short Colloquial PostingsMoisés Goldszmidt, Marc Najork, Stelios Paparizos. 95-111 [doi]
• A Pairwise Label Ranking Method with Imprecise Scores and Partial PredictionsSébastien Destercke. 112-127 [doi]
• Learning Socially Optimal Information Systems from Egoistic UsersKarthik Raman, Thorsten Joachims. 128-144 [doi]
• Socially Enabled Preference Learning from Implicit Feedback DataJulien Delporte, Alexandros Karatzoglou, Tomasz Matuszczyk, Stéphane Canu. 145-160 [doi]
• Cross-Domain Recommendation via Cluster-Level Latent Factor ModelSheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick Gallinari, Jun Guo. 161-176 [doi]
• Minimal Shrinkage for Noisy Data Recovery Using Schatten-p Norm ObjectiveDeguang Kong, Miao Zhang, Chris H. Q. Ding. 177-193 [doi]
• Noisy Matrix Completion Using Alternating MinimizationSuriya Gunasekar, Ayan Acharya, Neeraj Gaur, Joydeep Ghosh. 194-209 [doi]
• A Nearly Unbiased Matrix Completion ApproachDehua Liu, Tengfei Zhou, Hui Qian, Congfu Xu, Zhihua Zhang. 210-225 [doi]
• A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of RankHongyang Zhang, Zhouchen Lin, Chao Zhang. 226-241 [doi]
• Efficient Rank-one Residue Approximation Method for Graph Regularized Non-negative Matrix FactorizationQing Liao, Qian Zhang. 242-255 [doi]
• Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued DataKleanthis-Nikolaos Kontonasios, Jilles Vreeken, Tijl De Bie. 256-271 [doi]
• An Analysis of Tensor Models for Learning on Structured DataMaximilian Nickel, Volker Tresp. 272-287 [doi]
• Learning Modewise Independent Components from Tensor Data Using Multilinear Mixing ModelHaiping Lu. 288-303 [doi]
• Taxonomic Prediction with Tree-Structured CovariancesMatthew B. Blaschko, Wojciech Zaremba, Arthur Gretton. 304-319 [doi]
• Position Preserving Multi-Output PredictionZubin Abraham, Pang-Ning Tan, Perdinan, Julie Winkler, Shiyuan Zhong, Malgorzata Liszewska. 320-335 [doi]
• Structured Output Learning with Candidate Labels for Local PartsChengtao Li, Jianwen Zhang, Zheng Chen. 336-352 [doi]
• Shared Structure Learning for Multiple Tasks with Multiple ViewsXin Jin, Fuzhen Zhuang, Shuhui Wang, Qing He, Zhongzhi Shi. 353-368 [doi]
• Using Both Latent and Supervised Shared Topics for Multitask LearningAyan Acharya, Aditya Rawal, Raymond J. Mooney, Eduardo R. Hruschka. 369-384 [doi]
• Probabilistic Clustering for Hierarchical Multi-Label Classification of Protein FunctionsRodrigo C. Barros, Ricardo Cerri, Alex Alves Freitas, André Carlos Ponce de Leon Ferreira de Carvalho. 385-400 [doi]
• Multi-core Structural SVM TrainingKai-Wei Chang, Vivek Srikumar, Dan Roth. 401-416 [doi]
• Multi-label Classification with Output KernelsYuhong Guo, Dale Schuurmans. 417-432 [doi]
• Boosting for Unsupervised Domain AdaptationAmaury Habrard, Jean-Philippe Peyrache, Marc Sebban. 433-448 [doi]
• Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann MachinesHaitham Bou-Ammar, Decebal Constantin Mocanu, Matthew E. Taylor, Kurt Driessens, Karl Tuyls, Gerhard Weiss. 449-464 [doi]
• A Layered Dirichlet Process for Hierarchical Segmentation of Sequential Grouped DataAdway Mitra, Ranganath B. N., Indrajit Bhattacharya. 465-482 [doi]
• A Bayesian Classifier for Learning from Tensorial DataWei Liu, Jeffrey Chan, James Bailey, Christopher Leckie, Fang Chen, Kotagiri Ramamohanarao. 483-498 [doi]
• Prediction with Model-Based NeutralityKazuto Fukuchi, Jun Sakuma, Toshihiro Kamishima. 499-514 [doi]
• Decision-Theoretic Sparsification for Gaussian Process Preference LearningM. Ehsan Abbasnejad, Edwin V. Bonilla, Scott Sanner. 515-530 [doi]
• Variational Hidden Conditional Random Fields with Coupled Dirichlet Process MixturesKonstantinos Bousmalis, Stefanos Zafeiriou, Louis-Philippe Morency, Maja Pantic, Zoubin Ghahramani. 531-547 [doi]
• Sparsity in Bayesian Blind Source Separation and DeconvolutionVáclav Smídl, Ondrej Tichy. 548-563 [doi]
• Nested Hierarchical Dirichlet Process for Nonparametric Entity-Topic AnalysisPriyanka Agrawal, Lavanya Sita Tekumalla, Indrajit Bhattacharya. 564-579 [doi]
• Knowledge Intensive Learning: Combining Qualitative Constraints with Causal Independence for Parameter Learning in Probabilistic ModelsShuo Yang, Sriraam Natarajan. 580-595 [doi]
• Direct Learning of Sparse Changes in Markov Networks by Density Ratio EstimationSong Liu, John A. Quinn, Michael U. Gutmann, Masashi Sugiyama. 596-611 [doi]
• Greedy Part-Wise Learning of Sum-Product NetworksRobert Peharz, Bernhard C. Geiger, Franz Pernkopf. 612-627 [doi]
• From Topic Models to Semi-supervised Learning: Biasing Mixed-Membership Models to Exploit Topic-Indicative Features in Entity ClusteringRamnath Balasubramanyan, Bhavana Bharat Dalvi, William W. Cohen. 628-642 [doi]
• Hub Co-occurrence Modeling for Robust High-Dimensional kNN ClassificationNenad Tomasev, Dunja Mladenic. 643-659 [doi]
• Fast kNN Graph Construction with Locality Sensitive HashingYan-Ming Zhang, Kaizhu Huang, Guanggang Geng, Cheng-Lin Liu. 660-674 [doi]
• Mixtures of Large Margin Nearest Neighbor ClassifiersMurat Semerci, Ethem Alpaydin. 675-688 [doi]