Table of Contents

• The Randomized Dependence CoefficientDavid López-Paz, Philipp Hennig, Bernhard Schölkopf. 1-9 [doi]
• Documents as multiple overlapping windows into grids of countsAlessandro Perina, Nebojsa Jojic, Manuele Bicego, Andrzej Truski. 10-18 [doi]
• Reciprocally Coupled Local Estimators Implement Bayesian Information Integration DistributivelyWenhao Zhang, Si Wu. 19-27 [doi]
• Latent Maximum Margin ClusteringGuang-Tong Zhou, Tian Lan, Arash Vahdat, Greg Mori. 28-36 [doi]
• Data-driven Distributionally Robust Polynomial OptimizationMartin Mevissen, Emanuele Ragnoli, Jia Yuan Yu. 37-45 [doi]
• Transfer Learning in a Transductive SettingMarcus Rohrbach, Sandra Ebert, Bernt Schiele. 46-54 [doi]
• Bayesian optimization explains human active searchAli Borji, Laurent Itti. 55-63 [doi]
• Provable Subspace Clustering: When LRR meets SSCYu-Xiang Wang, Huan Xu, Chenlei Leng. 64-72 [doi]
• Generalized Random Utility Models with Multiple TypesHossein Azari Soufiani, Hansheng Diao, Zhenyu Lai, David C. Parkes. 73-81 [doi]
• Polar Operators for Structured Sparse EstimationXinhua Zhang, Yaoliang Yu, Dale Schuurmans. 82-90 [doi]
• On Decomposing the Proximal MapYaoliang Yu. 91-99 [doi]
• Point Based Value Iteration with Optimal Belief Compression for Dec-POMDPsLiam MacDermed, Charles L. Isbell. 100-108 [doi]
• PAC-Bayes-Empirical-Bernstein InequalityIlya O. Tolstikhin, Yevgeny Seldin. 109-117 [doi]
• Modeling Clutter Perception using Parametric Proto-object PartitioningChen-Ping Yu, Wen-Yu Hua, Dimitris Samaras, Gregory J. Zelinsky. 118-126 [doi]
• Robust Multimodal Graph Matching: Sparse Coding Meets Graph MatchingMarcelo Fiori, Pablo Sprechmann, Joshua T. Vogelstein, Pablo Musé, Guillermo Sapiro. 127-135 [doi]
• Transportability from Multiple Environments with Limited ExperimentsElias Bareinboim, Sanghack Lee, Vasant Honavar, Judea Pearl. 136-144 [doi]
• More data speeds up training time in learning halfspaces over sparse vectorsAmit Daniely, Nati Linial, Shai Shalev-Shwartz. 145-153 [doi]
• Causal Inference on Time Series using Restricted Structural Equation ModelsJonas Peters, Dominik Janzing, Bernhard Schölkopf. 154-162 [doi]
• Deep Fisher Networks for Large-Scale Image ClassificationKaren Simonyan, Andrea Vedaldi, Andrew Zisserman. 163-171 [doi]
• Sparse Additive Text Models with Low Rank BackgroundLei Shi. 172-180 [doi]
• Variance Reduction for Stochastic Gradient OptimizationChong Wang, Xi Chen, Alex J. Smola, Eric P. Xing. 181-189 [doi]
• Training and Analysing Deep Recurrent Neural NetworksMichiel Hermans, Benjamin Schrauwen. 190-198 [doi]
• A simple example of Dirichlet process mixture inconsistency for the number of componentsJeffrey W. Miller, Matthew T. Harrison. 199-206 [doi]
• Variational Policy Search via Trajectory OptimizationSergey Levine, Vladlen Koltun. 207-215 [doi]
• Scalable kernels for graphs with continuous attributesAasa Feragen, Niklas Kasenburg, Jens Petersen, Marleen de Bruijne, Karsten M. Borgwardt. 216-224 [doi]
• Density estimation from unweighted k-nearest neighbor graphs: a roadmapUlrike von Luxburg, Morteza Alamgir. 225-233 [doi]
• Decision Jungles: Compact and Rich Models for ClassificationJamie Shotton, Toby Sharp, Pushmeet Kohli, Sebastian Nowozin, John M. Winn, Antonio Criminisi. 234-242 [doi]
• What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative ApproachZhenwen Dai, Georgios Exarchakis, Jörg Lücke. 243-251 [doi]
• Actor-Critic Algorithms for Risk-Sensitive MDPsPrashanth L. A., Mohammad Ghavamzadeh. 252-260 [doi]
• Summary Statistics for Partitionings and Feature AllocationsIsik Baris Fidaner, Ali Taylan Cemgil. 261-269 [doi]
• One-shot learning and big data with n=2Lee H. Dicker, Dean P. Foster. 270-278 [doi]
• Variational Inference for Mahalanobis Distance Metrics in Gaussian Process RegressionMichalis K. Titsias, Miguel Lázaro-Gredilla. 279-287 [doi]
• Correlations strike back (again): the case of associative memory retrievalCristina Savin, Peter Dayan, Máté Lengyel. 288-296 [doi]
• Optimal Neural Population Codes for High-dimensional Stimulus VariablesZhuo Wang, Alan A. Stocker, Daniel D. Lee. 297-305 [doi]
• Online Variational Approximations to non-Exponential Family Change Point Models: With Application to Radar TrackingRyan D. Turner, Steven Bottone, Clay J. Stanek. 306-314 [doi]
• Accelerating Stochastic Gradient Descent using Predictive Variance ReductionRie Johnson, Tong Zhang 0001. 315-323 [doi]
• Using multiple samples to learn mixture modelsJason D. Lee, Ran Gilad-Bachrach, Rich Caruana. 324-332 [doi]
• Learning Hidden Markov Models from Non-sequence Data via Tensor DecompositionTzu-Kuo Huang, Jeff Schneider. 333-341 [doi]
• On model selection consistency of penalized M-estimators: a geometric theoryJason D. Lee, Yuekai Sun, Jonathan E. Taylor. 342-350 [doi]
• Dropout Training as Adaptive RegularizationStefan Wager, Sida Wang, Percy Liang. 351-359 [doi]
• New Subsampling Algorithms for Fast Least Squares RegressionParamveer S. Dhillon, Yichao Lu, Dean P. Foster, Lyle H. Ungar. 360-368 [doi]
• Faster Ridge Regression via the Subsampled Randomized Hadamard TransformYichao Lu, Paramveer S. Dhillon, Dean P. Foster, Lyle H. Ungar. 369-377 [doi]
• Accelerated Mini-Batch Stochastic Dual Coordinate AscentShai Shalev-Shwartz, Tong Zhang 0001. 378-385 [doi]
• Improved and Generalized Upper Bounds on the Complexity of Policy IterationBruno Scherrer. 386-394 [doi]
• Online Learning of Nonparametric Mixture Models via Sequential Variational ApproximationDahua Lin. 395-403 [doi]
• Online Robust PCA via Stochastic OptimizationJiashi Feng, Huan Xu, Shuicheng Yan. 404-412 [doi]
• Least Informative DimensionsFabian H. Sinz, Anna Stockl, Jan Grewe, Jan Benda. 413-421 [doi]
• A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale NetworksJunming Yin, Qirong Ho, Eric P. Xing. 422-430 [doi]
• Understanding variable importances in forests of randomized treesGilles Louppe, Louis Wehenkel, Antonio Sutera, Pierre Geurts. 431-439 [doi]
• Correlated random features for fast semi-supervised learningBrian McWilliams, David Balduzzi, Joachim M. Buhmann. 440-448 [doi]
• Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process MixtureTrevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How, Lawrence Carin. 449-457 [doi]
• Better Approximation and Faster Algorithm Using the Proximal AverageYaoliang Yu. 458-466 [doi]
• Rapid Distance-Based Outlier Detection via SamplingMahito Sugiyama, Karsten M. Borgwardt. 467-475 [doi]
• Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optimaPo-Ling Loh, Martin J. Wainwright. 476-484 [doi]
• Non-Linear Domain Adaptation with BoostingCarlos J. Becker, C. Mario Christoudias, Pascal Fua. 485-493 [doi]
• Mid-level Visual Element Discovery as Discriminative Mode SeekingCarl Doersch, Abhinav Gupta, Alexei A. Efros. 494-502 [doi]
• q-OCSVM: A q-Quantile Estimator for High-Dimensional DistributionsAssaf Glazer, Michael Lindenbaum, Shaul Markovitch. 503-511 [doi]
• Auditing: Active Learning with Outcome-Dependent Query CostsSivan Sabato, Anand D. Sarwate, Nati Srebro. 512-520 [doi]
• A message-passing algorithm for multi-agent trajectory planningJosé Bento, Nate Derbinsky, Javier Alonso-Mora, Jonathan S. Yedidia. 521-529 [doi]
• Learning Stochastic Feedforward Neural NetworksYichuan Tang, Ruslan Salakhutdinov. 530-538 [doi]
• Inferring neural population dynamics from multiple partial recordings of the same neural circuitSrinivas C. Turaga, Lars Buesing, Adam M. Packer, Henry Dalgleish, Noah Pettit, Michael Häusser, Jakob H. Macke. 539-547 [doi]
• Multi-Prediction Deep Boltzmann MachinesIan J. Goodfellow, Mehdi Mirza, Aaron C. Courville, Yoshua Bengio. 548-556 [doi]
• Higher Order Priors for Joint Intrinsic Image, Objects, and Attributes EstimationVibhav Vineet, Carsten Rother, Philip H. S. Torr. 557-565 [doi]
• Blind Calibration in Compressed Sensing using Message Passing AlgorithmsChristophe Schülke, Francesco Caltagirone, Florent Krzakala, Lenka Zdeborová. 566-574 [doi]
• Learning Trajectory Preferences for Manipulators via Iterative ImprovementAshesh Jain, Brian Wojcik, Thorsten Joachims, Ashutosh Saxena. 575-583 [doi]
• Large Scale Distributed Sparse Precision EstimationHuahua Wang, Arindam Banerjee, Cho-Jui Hsieh, Pradeep D. Ravikumar, Inderjit S. Dhillon. 584-592 [doi]
• Neural representation of action sequences: how far can a simple snippet-matching model take us?Cheston Tan, Jedediah M. Singer, Thomas Serre, David Sheinberg, Tomaso Poggio. 593-601 [doi]
• On Algorithms for Sparse Multi-factor NMFSiwei Lyu, Xin Wang. 602-610 [doi]
• Dirty Statistical ModelsEunho Yang, Pradeep D. Ravikumar. 611-619 [doi]
• Parallel Sampling of DP Mixture Models using Sub-Cluster SplitsJason Chang, John W. Fisher III. 620-628 [doi]
• Trading Computation for Communication: Distributed Stochastic Dual Coordinate AscentTianbao Yang. 629-637 [doi]
• Prior-free and prior-dependent regret bounds for Thompson SamplingSébastien Bubeck, Che-Yu Liu. 638-646 [doi]
• Structured Learning via Logistic RegressionJustin Domke. 647-655 [doi]
• Which Space Partitioning Tree to Use for Search?Parikshit Ram, Alexander G. Gray. 656-664 [doi]
• Projecting Ising Model Parameters for Fast MixingJustin Domke, Xianghang Liu. 665-673 [doi]
• Mixed Optimization for Smooth FunctionsMehrdad Mahdavi, Lijun Zhang 0005, Rong Jin. 674-682 [doi]
• Conditional Random Fields via Univariate Exponential FamiliesEunho Yang, Pradeep D. Ravikumar, Genevera I. Allen, Zhandong Liu. 683-691 [doi]
• Stochastic blockmodel approximation of a graphon: Theory and consistent estimationEdoardo M. Airoldi, Thiago B. Costa, Stanley H. Chan. 692-700 [doi]
• Reinforcement Learning in Robust Markov Decision ProcessesShiau Hong Lim, Huan Xu, Shie Mannor. 701-709 [doi]
• On the Linear Convergence of the Proximal Gradient Method for Trace Norm RegularizationKe Hou, Zirui Zhou, Anthony Man-Cho So, Zhi-Quan Luo. 710-718 [doi]
• Recurrent networks of coupled Winner-Take-All oscillators for solving constraint satisfaction problemsHesham Mostafa, Lorenz. K. Müller, Giacomo Indiveri. 719-727 [doi]
• Latent Structured Active LearningWenjie Luo, Alexander G. Schwing, Raquel Urtasun. 728-736 [doi]
• A Gang of BanditsNicolò Cesa-Bianchi, Claudio Gentile, Giovanni Zappella. 737-745 [doi]
• Learning Feature Selection Dependencies in Multi-task LearningDaniel Hernández-Lobato, José Miguel Hernández-Lobato. 746-754 [doi]
• B-test: A Non-parametric, Low Variance Kernel Two-sample TestWojciech Zaremba, Arthur Gretton, Matthew B. Blaschko. 755-763 [doi]
• Online PCA for Contaminated DataJiashi Feng, Huan Xu, Shie Mannor, Shuicheng Yan. 764-772 [doi]
• Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)Francis Bach, Eric Moulines. 773-781 [doi]
• Efficient Algorithm for Privately Releasing Smooth QueriesZiteng Wang, Kai Fan, Jiaqi Zhang, Liwei Wang. 782-790 [doi]
• k-Way Similarity SearchAnshumali Shrivastava, Ping Li 0001. 791-799 [doi]
• Unsupervised Spectral Learning of Finite State TransducersRaphaël Bailly, Xavier Carreras, Ariadna Quattoni. 800-808 [doi]
• Learning a Deep Compact Image Representation for Visual TrackingNaiyan Wang, Dit-Yan Yeung. 809-817 [doi]
• Learning Multi-level Sparse RepresentationsFerran Diego Andilla, Fred A. Hamprecht. 818-826 [doi]
• Robust Data-Driven Dynamic ProgrammingGrani Adiwena Hanasusanto, Daniel Kuhn. 827-835 [doi]
• Low-Rank Matrix and Tensor Completion via Adaptive SamplingAkshay Krishnamurthy, Aarti Singh. 836-844 [doi]
• Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization AlgorithmsAdrien Todeschini, François Caron, Marie Chavent. 845-853 [doi]
• Distributed Exploration in Multi-Armed BanditsEshcar Hillel, Zohar Shay Karnin, Tomer Koren, Ronny Lempel, Oren Somekh. 854-862 [doi]
• The Pareto Regret FrontierWouter M. Koolen. 863-871 [doi]
• Direct 0-1 Loss Minimization and Margin Maximization with BoostingShaodan Zhai, Tian Xia, Ming Tan, Shaojun Wang. 872-880 [doi]
• Regret based Robust Solutions for Uncertain Markov Decision ProcessesAsrar Ahmed, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet. 881-889 [doi]
• Speeding up Permutation Testing in NeuroimagingChris Hinrichs, Vamsi Ithapu, Qinyuan Sun, Sterling C. Johnson, Vikas Singh. 890-898 [doi]
• Generalized Denoising Auto-Encoders as Generative ModelsYoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent. 899-907 [doi]
• Supervised Sparse Analysis and Synthesis OperatorsPablo Sprechmann, Roee Litman, Tal Ben Yakar, Alexander M. Bronstein, Guillermo Sapiro. 908-916 [doi]
• Low-rank matrix reconstruction and clustering via approximate message passingRyosuke Matsushita, Toshiyuki Tanaka. 917-925 [doi]
• Reasoning With Neural Tensor Networks for Knowledge Base CompletionRichard Socher, Danqi Chen, Christopher D. Manning, Andrew Y. Ng. 926-934 [doi]
• Zero-Shot Learning Through Cross-Modal TransferRichard Socher, Milind Ganjoo, Christopher D. Manning, Andrew Y. Ng. 935-943 [doi]
• Estimating LASSO Risk and Noise LevelMohsen Bayati, Murat A. Erdogdu, Andrea Montanari. 944-952 [doi]
• Learning Adaptive Value of Information for Structured PredictionDavid J. Weiss, Ben Taskar. 953-961 [doi]
• Efficient Online Inference for Bayesian Nonparametric Relational ModelsDae-Il Kim, Prem Gopalan, David M. Blei, Erik B. Sudderth. 962-970 [doi]
• Approximate inference in latent Gaussian-Markov models from continuous time observationsBotond Cseke, Manfred Opper, Guido Sanguinetti. 971-979 [doi]
• Linear Convergence with Condition Number Independent Access of Full GradientsLijun Zhang 0005, Mehrdad Mahdavi, Rong Jin. 980-988 [doi]
• When in Doubt, SWAP: High-Dimensional Sparse Recovery from Correlated MeasurementsDivyanshu Vats, Richard G. Baraniuk. 989-997 [doi]
• Wavelets on Graphs via Deep LearningRaif M. Rustamov, Leonidas J. Guibas. 998-1006 [doi]
• Robust Spatial Filtering with Beta DivergenceWojciech Samek, Duncan A. J. Blythe, Klaus-Robert Müller, Motoaki Kawanabe. 1007-1015 [doi]
• Convex Relaxations for Permutation ProblemsFajwel Fogel, Rodolphe Jenatton, Francis Bach, Alexandre d'Aspremont. 1016-1024 [doi]
• High-Dimensional Gaussian Process BanditsJosip Djolonga, Andreas Krause, Volkan Cevher. 1025-1033 [doi]
• A memory frontier for complex synapsesSubhaneil Lahiri, Surya Ganguli. 1034-1042 [doi]
• Marginals-to-Models ReducibilityTim Roughgarden, Michael Kearns. 1043-1051 [doi]
• First-order Decomposition TreesNima Taghipour, Jesse Davis, Hendrik Blockeel. 1052-1060 [doi]
• A Comparative Framework for Preconditioned Lasso AlgorithmsFabian L. Wauthier, Nebojsa Jojic, Michael I. Jordan. 1061-1069 [doi]
• Lasso Screening Rules via Dual Polytope ProjectionJie Wang, Jiayu Zhou, Peter Wonka, Jieping Ye. 1070-1078 [doi]
• Binary to Bushy: Bayesian Hierarchical Clustering with the Beta CoalescentYuening Hu, Jordan L. Boyd-Graber, Hal Daumé III, Z. Irene Ying. 1079-1087 [doi]
• A Latent Source Model for Nonparametric Time Series ClassificationGeorge H. Chen, Stanislav Nikolov, Devavrat Shah. 1088-1096 [doi]
• Efficient Optimization for Sparse Gaussian Process RegressionYanshuai Cao, Marcus A. Brubaker, David J. Fleet, Aaron Hertzmann. 1097-1105 [doi]
• Lexical and Hierarchical Topic RegressionViet-An Nguyen, Jordan L. Boyd-Graber, Philip Resnik. 1106-1114 [doi]
• Stochastic Convex Optimization with Multiple ObjectivesMehrdad Mahdavi, Tianbao Yang, Rong Jin. 1115-1123 [doi]
• A Kernel Test for Three-Variable InteractionsDino Sejdinovic, Arthur Gretton, Wicher Bergsma. 1124-1132 [doi]
• Memoized Online Variational Inference for Dirichlet Process Mixture ModelsMichael C. Hughes, Erik B. Sudderth. 1133-1141 [doi]
• Designed Measurements for Vector Count DataLiming Wang, David E. Carlson, Miguel R. D. Rodrigues, David Wilcox, A. Robert Calderbank, Lawrence Carin. 1142-1150 [doi]
• Robust Transfer Principal Component Analysis with Rank ConstraintsYuhong Guo. 1151-1159 [doi]
• Online Learning with Switching Costs and Other Adaptive AdversariesNicolò Cesa-Bianchi, Ofer Dekel, Ohad Shamir. 1160-1168 [doi]
• Learning Prices for Repeated Auctions with Strategic BuyersKareem Amin, Afshin Rostamizadeh, Umar Syed. 1169-1177 [doi]
• Probabilistic Principal Geodesic AnalysisMiaomiao Zhang, P. Thomas Fletcher. 1178-1186 [doi]
• Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical ModelsAdel Javanmard, Andrea Montanari. 1187-1195 [doi]
• Learning with Noisy LabelsNagarajan Natarajan, Inderjit S. Dhillon, Pradeep D. Ravikumar, Ambuj Tewari. 1196-1204 [doi]
• Tracking Time-varying Graphical StructureErich Kummerfeld, David Danks. 1205-1213 [doi]
• Factorized Asymptotic Bayesian Inference for Latent Feature ModelsKohei Hayashi, Ryohei Fujimaki. 1214-1222 [doi]
• More Effective Distributed ML via a Stale Synchronous Parallel Parameter ServerQirong Ho, James Cipar, Henggang Cui, Seunghak Lee, Jin Kyu Kim, Phillip B. Gibbons, Garth A. Gibson, Gregory R. Ganger, Eric P. Xing. 1223-1231 [doi]
• Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical ModelsJie Liu, David Page. 1232-1240 [doi]
• Online Learning with Costly Features and LabelsNavid Zolghadr, Gábor Bartók, Russell Greiner, András György, Csaba Szepesvári. 1241-1249 [doi]
• Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitionsEftychios A. Pnevmatikakis, Liam Paninski. 1250-1258 [doi]
• A Novel Two-Step Method for Cross Language Representation LearningMin Xiao, Yuhong Guo. 1259-1267 [doi]
• On Sampling from the Gibbs Distribution with Random Maximum A-Posteriori PerturbationsTamir Hazan, Subhransu Maji, Tommi Jaakkola. 1268-1276 [doi]
• Graphical Models for Inference with Missing DataKarthika Mohan, Judea Pearl, Jin Tian. 1277-1285 [doi]
• Reshaping Visual Datasets for Domain AdaptationBoqing Gong, Kristen Grauman, Fei Sha. 1286-1294 [doi]
• Statistical Active Learning AlgorithmsMaria-Florina Balcan, Vitaly Feldman. 1295-1303 [doi]
• Bayesian Inference and Online Experimental Design for Mapping Neural MicrocircuitsBenjamin Shababo, Timothy Brooks Paige, Ari Pakman, Liam Paninski. 1304-1312 [doi]
• Reflection methods for user-friendly submodular optimizationStefanie Jegelka, Francis Bach, Suvrit Sra. 1313-1321 [doi]
• Unsupervised Structure Learning of Stochastic And-Or GrammarsKewei Tu, Maria Pavlovskaia, Song Chun Zhu. 1322-1330 [doi]
• Convex Tensor Decomposition via Structured Schatten Norm RegularizationRyota Tomioka, Taiji Suzuki. 1331-1339 [doi]
• Stochastic Ratio Matching of RBMs for Sparse High-Dimensional InputsYann Dauphin, Yoshua Bengio. 1340-1348 [doi]
• Learning Chordal Markov Networks by Constraint SatisfactionJukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar. 1349-1357 [doi]
• Parametric Task LearningIchiro Takeuchi, Tatsuya Hongo, Masashi Sugiyama, Shinichi Nakajima. 1358-1366 [doi]
• A Deep Architecture for Matching Short TextsZhengdong Lu, Hang Li. 1367-1375 [doi]
• Computing the Stationary Distribution LocallyChristina E. Lee, Asuman E. Ozdaglar, Devavrat Shah. 1376-1384 [doi]
• Nonparametric Multi-group Membership Model for Dynamic NetworksMyunghwan Kim 0002, Jure Leskovec. 1385-1393 [doi]
• Adaptive Step-Size for Policy Gradient MethodsMatteo Pirotta, Marcello Restelli, Luca Bascetta. 1394-1402 [doi]
• Optimistic Concurrency Control for Distributed Unsupervised LearningXinghao Pan, Joseph E. Gonzalez, Stefanie Jegelka, Tamara Broderick, Michael I. Jordan. 1403-1411 [doi]
• Reservoir Boosting : Between Online and Offline Ensemble LearningLeonidas Lefakis, François Fleuret. 1412-1420 [doi]
• Multiclass Total Variation ClusteringXavier Bresson, Thomas Laurent 0001, David Uminsky, James H. von Brecht. 1421-1429 [doi]
• Approximate Inference in Continuous Determinantal ProcessesRaja Hafiz Affandi, Emily B. Fox, Ben Taskar. 1430-1438 [doi]
• Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace ClusteringShinichi Nakajima, Akiko Takeda, S. Derin Babacan, Masashi Sugiyama, Ichiro Takeuchi. 1439-1447 [doi]
• Thompson Sampling for 1-Dimensional Exponential Family BanditsNathaniel Korda, Emilie Kaufmann, Rémi Munos. 1448-1456 [doi]
• Active Learning for Probabilistic Hypotheses Using the Maximum Gibbs Error CriterionViet Cuong Nguyen, Wee Sun Lee, Nan Ye, Kian Ming Adam Chai, Hai Leong Chieu. 1457-1465 [doi]
• It is all in the noise: Efficient multi-task Gaussian process inference with structured residualsBarbara Rakitsch, Christoph Lippert, Karsten M. Borgwardt, Oliver Stegle. 1466-1474 [doi]
• Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking LossesHarish G. Ramaswamy, Shivani Agarwal, Ambuj Tewari. 1475-1483 [doi]
• Inverse Density as an Inverse Problem: the Fredholm Equation ApproachQichao Que, Mikhail Belkin. 1484-1492 [doi]
• Robust Image Denoising with Multi-Column Deep Neural NetworksForest Agostinelli, Michael R. Anderson, Honglak Lee. 1493-1501 [doi]
• EDML for Learning Parameters in Directed and Undirected Graphical ModelsKhaled S. Refaat, Arthur Choi, Adnan Darwiche. 1502-1510 [doi]
• Similarity Component AnalysisSoravit Changpinyo, Kuan Liu, Fei Sha. 1511-1519 [doi]
• Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics ProgramsVikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum. 1520-1528 [doi]
• Local Privacy and Minimax Bounds: Sharp Rates for Probability EstimationJohn C. Duchi, Martin J. Wainwright, Michael I. Jordan. 1529-1537 [doi]
• Firing rate predictions in optimal balanced networksDavid G. T. Barrett, Sophie Denève, Christian K. Machens. 1538-1546 [doi]
• Manifold-based Similarity Adaptation for Label PropagationMasayuki Karasuyama, Hiroshi Mamitsuka. 1547-1555 [doi]
• Non-Uniform Camera Shake Removal Using a Spatially-Adaptive Sparse PenaltyHaichao Zhang, David P. Wipf. 1556-1564 [doi]
• Near-Optimal Entrywise Sampling for Data MatricesDimitris Achlioptas, Zohar Shay Karnin, Edo Liberty. 1565-1573 [doi]
• Learning to Prune in Metric and Non-Metric SpacesLeonid Boytsov, Bilegsaikhan Naidan. 1574-1582 [doi]
• Online learning in episodic Markovian decision processes by relative entropy policy searchAlexander Zimin, Gergely Neu. 1583-1591 [doi]
• Optimistic policy iteration and natural actor-critic: A unifying view and a non-optimality resultPaul Wagner. 1592-1600 [doi]
• Bayesian Hierarchical Community DiscoveryCharles Blundell, Yee Whye Teh. 1601-1609 [doi]
• From Bandits to Experts: A Tale of Domination and IndependenceNoga Alon, Nicolò Cesa-Bianchi, Claudio Gentile, Yishay Mansour. 1610-1618 [doi]
• Predictive PAC Learning and Process DecompositionsCosma Rohilla Shalizi, Aryeh Kontorovitch. 1619-1627 [doi]
• Pass-efficient unsupervised feature selectionCrystal Maung, Haim Schweitzer. 1628-1636 [doi]
• Simultaneous Rectification and Alignment via Robust Recovery of Low-rank TensorsXiaoqin Zhang, Di Wang, Zhengyuan Zhou, Yi Ma. 1637-1645 [doi]
• Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree SearchAijun Bai, Feng Wu, Xiaoping Chen. 1646-1654 [doi]
• Solving inverse problem of Markov chain with partial observationsTetsuro Morimura, Takayuki Osogami, Tsuyoshi Idé. 1655-1663 [doi]
• Locally Adaptive Bayesian Multivariate Time SeriesDaniele Durante, Bruno Scarpa, David B. Dunson. 1664-1672 [doi]
• Mapping paradigm ontologies to and from the brainYannick Schwartz, Bertrand Thirion, Gaël Varoquaux. 1673-1681 [doi]
• Noise-Enhanced Associative MemoriesAmin Karbasi, Amir Hesam Salavati, Amin Shokrollahi, Lav R. Varshney. 1682-1690 [doi]
• Exact and Stable Recovery of Pairwise Interaction TensorsShouyuan Chen, Michael R. Lyu, Irwin King, Zenglin Xu. 1691-1699 [doi]
• Bayesian entropy estimation for binary spike train data using parametric prior knowledgeEvan Archer, Il Memming Park, Jonathan W. Pillow. 1700-1708 [doi]
• Perfect Associative Learning with Spike-Timing-Dependent PlasticityChristian Albers, Maren Westkott, Klaus Pawelzik. 1709-1717 [doi]
• On Poisson Graphical ModelsEunho Yang, Pradeep D. Ravikumar, Genevera I. Allen, Zhandong Liu. 1718-1726 [doi]
• Streaming Variational BayesTamara Broderick, Nicholas Boyd, Andre Wibisono, Ashia C. Wilson, Michael I. Jordan. 1727-1735 [doi]
• Gaussian Process Conditional Copulas with Applications to Financial Time SeriesJosé Miguel Hernández-Lobato, James Robert Lloyd, Daniel Hernández-Lobato. 1736-1744 [doi]
• Extracting regions of interest from biological images with convolutional sparse block codingMarius Pachitariu, Adam M. Packer, Noah Pettit, Henry Dalgleish, Michael Häusser, Maneesh Sahani. 1745-1753 [doi]
• Approximate Dynamic Programming Finally Performs Well in the Game of TetrisVictor Gabillon, Mohammad Ghavamzadeh, Bruno Scherrer. 1754-1762 [doi]
• Third-Order Edge Statistics: Contour Continuation, Curvature, and Cortical ConnectionsMatthew Lawlor, Steven W. Zucker. 1763-1771 [doi]
• DESPOT: Online POMDP Planning with RegularizationAdhiraj Somani, Nan Ye, David Hsu, Wee Sun Lee. 1772-1780 [doi]
• Matrix Completion From any Given Set of ObservationsTroy Lee, Adi Shraibman. 1781-1787 [doi]
• Regression-tree Tuning in a Streaming SettingSamory Kpotufe, Francesco Orabona. 1788-1796 [doi]
• Multiscale Dictionary Learning for Estimating Conditional DistributionsFrancesca Petralia, Joshua T. Vogelstein, David B. Dunson. 1797-1805 [doi]
• Dimension-Free Exponentiated GradientFrancesco Orabona. 1806-1814 [doi]
• Stochastic Optimization of PCA with Capped MSGRaman Arora, Andrew Cotter, Nati Srebro. 1815-1823 [doi]
• On Flat versus Hierarchical Classification in Large-Scale TaxonomiesRohit Babbar, Ioannis Partalas, Éric Gaussier, Massih-Reza Amini. 1824-1832 [doi]
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• Robust Bloom Filters for Large MultiLabel Classification TasksMoustapha Cissé, Nicolas Usunier, Thierry Artières, Patrick Gallinari. 1851-1859 [doi]
• Solving the multi-way matching problem by permutation synchronizationDeepti Pachauri, Risi Kondor, Vikas Singh. 1860-1868 [doi]
• Generalizing Analytic Shrinkage for Arbitrary Covariance StructuresDaniel Bartz, Klaus-Robert Müller. 1869-1877 [doi]
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• A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking DataJasper Snoek, Richard S. Zemel, Ryan Prescott Adams. 1932-1940 [doi]
• Robust Sparse Principal Component Regression under the High Dimensional Elliptical ModelFang Han, Han Liu. 1941-1949 [doi]
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• Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan StatisticJames Sharpnack, Akshay Krishnamurthy, Aarti Singh. 1959-1967 [doi]
• Demixing odors - fast inference in olfactionAgnieszka Grabska-Barwinska, Jeffrey M. Beck, Alexandre Pouget, Peter E. Latham. 1968-1976 [doi]
• Learning Multiple Models via Regularized WeightingDaniel Vainsencher, Shie Mannor, Huan Xu. 1977-1985 [doi]
• When are Overcomplete Topic Models Identifiable? Uniqueness of Tensor Tucker Decompositions with Structured SparsityAnima Anandkumar, Daniel Hsu, Majid Janzamin, Sham M. Kakade. 1986-1994 [doi]
• Distributed k-means and k-median clustering on general communication topologiesMaria-Florina Balcan, Steven Ehrlich, Yingyu Liang. 1995-2003 [doi]
• Multi-Task Bayesian OptimizationKevin Swersky, Jasper Snoek, Ryan Prescott Adams. 2004-2012 [doi]
• Online Learning of Dynamic Parameters in Social NetworksShahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie. 2013-2021 [doi]
• A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized CyclesJinwoo Shin, Andrew E. Gelfand, Michael Chertkov. 2022-2030 [doi]
• Learning with Invariance via Linear Functionals on Reproducing Kernel Hilbert SpaceXinhua Zhang, Wee Sun Lee, Yee Whye Teh. 2031-2039 [doi]
• Approximate Gaussian process inference for the drift function in stochastic differential equationsAndreas Ruttor, Philipp Batz, Manfred Opper. 2040-2048 [doi]
• Distributed Submodular Maximization: Identifying Representative Elements in Massive DataBaharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause. 2049-2057 [doi]
• Adaptive Market Making via Online LearningJacob Abernethy, Satyen Kale. 2058-2066 [doi]
• On the Sample Complexity of Subspace LearningAlessandro Rudi, Guillermo D. Cañas, Lorenzo Rosasco. 2067-2075 [doi]
• Spike train entropy-rate estimation using hierarchical Dirichlet process priorsKarin C. Knudson, Jonathan W. Pillow. 2076-2084 [doi]
• Embed and Project: Discrete Sampling with Universal HashingStefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman. 2085-2093 [doi]
• Discriminative Transfer Learning with Tree-based PriorsNitish Srivastava, Ruslan Salakhutdinov. 2094-2102 [doi]
• Small-Variance Asymptotics for Hidden Markov ModelsAnirban Roychowdhury, Ke Jiang, Brian Kulis. 2103-2111 [doi]
• Convergence of Monte Carlo Tree Search in Simultaneous Move GamesViliam Lisý, Vojtech Kovarík, Marc Lanctot, Branislav Bosanský. 2112-2120 [doi]
• DeViSE: A Deep Visual-Semantic Embedding ModelAndrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomas Mikolov. 2121-2129 [doi]
• Reward Mapping for Transfer in Long-Lived AgentsXiaoxiao Guo, Satinder P. Singh, Richard L. Lewis. 2130-2138 [doi]
• Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean SeparationMartin Azizyan, Aarti Singh, Larry A. Wasserman. 2139-2147 [doi]
• Predicting Parameters in Deep LearningMisha Denil, Babak Shakibi, Laurent Dinh, Marc'Aurelio Ranzato, Nando de Freitas. 2148-2156 [doi]
• Estimating the Unseen: Improved Estimators for Entropy and other PropertiesPaul Valiant, Gregory Valiant. 2157-2165 [doi]
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• RNADE: The real-valued neural autoregressive density-estimatorBenigno Uria, Iain Murray, Hugo Larochelle. 2175-2183 [doi]
• Two-Target Algorithms for Infinite-Armed Bandits with Bernoulli RewardsThomas Bonald, Alexandre Proutière. 2184-2192 [doi]
• Reconciling "priors" & "priors" without prejudice?Rémi Gribonval, Pierre Machart. 2193-2201 [doi]
• Sparse Overlapping Sets Lasso for Multitask Learning and its Application to fMRI AnalysisNikhil S. Rao, Christopher R. Cox, Robert D. Nowak, Timothy T. Rogers. 2202-2210 [doi]
• Sensor Selection in High-Dimensional Gaussian Trees with NuisancesDaniel S. Levine 0002, Jonathan P. How. 2211-2219 [doi]
• Sequential Transfer in Multi-armed Bandit with Finite Set of ModelsMohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill. 2220-2228 [doi]
• Buy-in-Bulk Active LearningLiu Yang, Jaime G. Carbonell. 2229-2237 [doi]
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• Message Passing Inference with Chemical Reaction NetworksNils Napp, Ryan Prescott Adams. 2247-2255 [doi]
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• Stochastic Majorization-Minimization Algorithms for Large-Scale OptimizationJulien Mairal. 2283-2291 [doi]
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• Fast Determinantal Point Process Sampling with Application to ClusteringByungkon Kang. 2319-2327 [doi]
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• Synthesizing Robust Plans under Incomplete Domain ModelsTuan Anh Nguyen 0001, Subbarao Kambhampati, Minh Binh Do. 2472-2480 [doi]
• Integrated Non-Factorized Variational InferenceShaobo Han, Xuejun Liao, Lawrence Carin. 2481-2489 [doi]
• Auxiliary-variable Exact Hamiltonian Monte Carlo Samplers for Binary DistributionsAri Pakman, Liam Paninski. 2490-2498 [doi]
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• One-shot learning by inverting a compositional causal processBrenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum. 2526-2534 [doi]
• Statistical analysis of coupled time series with Kernel Cross-Spectral Density operatorsMichel Besserve, Nikos K. Logothetis, Bernhard Schölkopf. 2535-2543 [doi]
• Fast Algorithms for Gaussian Noise Invariant Independent Component AnalysisJames R. Voss, Luis Rademacher, Mikhail Belkin. 2544-2552 [doi]
• Deep Neural Networks for Object DetectionChristian Szegedy, Alexander Toshev, Dumitru Erhan. 2553-2561 [doi]
• Geometric optimisation on positive definite matrices for elliptically contoured distributionsSuvrit Sra, Reshad Hosseini. 2562-2570 [doi]
• Sign Cauchy Projections and Chi-Square KernelPing Li 0001, Gennady Samorodnitsky, John E. Hopcroft. 2571-2579 [doi]
• Relevance Topic Model for Unstructured Social Group Activity RecognitionFang Zhao, Yongzhen Huang, Liang Wang, Tieniu Tan. 2580-2588 [doi]
• k-Prototype Learning for 3D Rigid StructuresHu Ding, Ronald Berezney, Jinhui Xu. 2589-2597 [doi]
• Restricting exchangeable nonparametric distributionsSinead Williamson, Steve N. MacEachern, Eric P. Xing. 2598-2606 [doi]
• Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit settingShunan Zhang, Angela J. Yu. 2607-2615 [doi]
• Probabilistic Movement PrimitivesAlexandros Paraschos, Christian Daniel, Jan Peters, Gerhard Neumann. 2616-2624 [doi]
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• Multilinear Dynamical Systems for Tensor Time SeriesMark Rogers, Lei Li, Stuart J. Russell. 2634-2642 [doi]
• Deep content-based music recommendationAäron Van Den Oord, Sander Dieleman, Benjamin Schrauwen. 2643-2651 [doi]
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• Analyzing Hogwild Parallel Gaussian Gibbs SamplingMatthew Johnson, James Saunderson, Alan S. Willsky. 2715-2723 [doi]
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