ICML 2015 - Lille

32nd International Conference on Machine Learning (ICML), Lille 2015

ICML 2015 is the leading international machine learning conference and is supported by the International Machine Learning Society (IMLS).

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Tutorials
6603 views, 2:04:30 Tutorial Natural Language Understanding: Foundations and State-of-the-ArtNatural Language Understanding: Foundations and State-of-the-Art Percy Liang Percy Liang 1 comment	4248 views, 1:10:55 Tutorial Advances in Structured PredictionAdvances in Structured Prediction Hal Daumé III Hal Daumé III	4060 views, 54:29 Tutorial Modern Convex Optimization Methods for Large-scale Empirical Risk MinimizationModern Convex Optimization Methods for Large-scale Empirical Risk Minimization Mark Schmidt Mark Schmidt	4075 views, 1:55:23 Tutorial Bayesian Time Series Modeling: Structured Representations for ScalabilityBayesian Time Series Modeling: Structured Representations for Scalability Emily Fox Emily Fox	3258 views, 2:01:20 Tutorial Computational Social ScienceComputational Social Science Hanna M. Wallach Hanna M. Wallach 1 comment
4121 views, 2:18:53 Tutorial Policy Search: Methods and ApplicationsPolicy Search: Methods and Applications Gerhard Neumann, Jan Peters Gerhard Neumann, Jan Peters
Welcome Address
3279 views, 09:27 Welcome addressWelcome address Joelle Pineau, David Blei, Francis R. Bach Joelle Pineau, David Blei, Francis R. Bach
Keynote Speakers
11752 views, 41:17 Keynote Two high stakes challenges in machine learningTwo high stakes challenges in machine learning Léon Bottou Léon Bottou	1577 views, 52:12 Keynote Learning Treatment Policies in Mobile HealthLearning Treatment Policies in Mobile Health Susan A. Murphy Susan A. Murphy	2304 views, 1:06:13 Keynote Social Interaction in Global NetworksSocial Interaction in Global Networks Jon Kleinberg Jon Kleinberg
Awards
1868 views, 19:07 Best Paper Award A Nearly-Linear Time Framework for Graph-Structured Sparsity A Nearly-Linear Time Framework for Graph-Structured Sparsity Ludwig Schmidt Ludwig Schmidt	3966 views, 15:09 Test of Time Award Learning to Rank Using Gradient DescentLearning to Rank Using Gradient Descent Chris Burges Chris Burges
Deep Learning I
2132 views, 15:58 Learning Program Embeddings to Propagate Feedback on Student CodeLearning Program Embeddings to Propagate Feedback on Student Code Chris Piech Chris Piech 1 comment	2012 views, 16:36 BilBOWA: Fast Bilingual Distributed Representations without Word AlignmentsBilBOWA: Fast Bilingual Distributed Representations without Word Alignments Stephan Gouws Stephan Gouws	2675 views, 15:44 Modeling Order in Neural Word Embeddings at ScaleModeling Order in Neural Word Embeddings at Scale David Gilmore, Andrew Trask David Gilmore, Andrew Trask 1 comment	2875 views, 18:02 Gated Feedback Recurrent Neural NetworksGated Feedback Recurrent Neural Networks Junyoung Chung Junyoung Chung	3201 views, 14:32 An Empirical Exploration of Recurrent Network ArchitecturesAn Empirical Exploration of Recurrent Network Architectures Rafal Jozefowicz Rafal Jozefowicz
Distributed Optimization
1762 views, 16:15 PASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate DescentPASSCoDe: Parallel ASynchronous Stochastic dual Co-ordinate Descent Cho-Jui Hsieh Cho-Jui Hsieh	2059 views, 14:27 An Asynchronous Distributed Proximal Gradient Method for Composite Convex OptimizationAn Asynchronous Distributed Proximal Gradient Method for Composite Convex Optimization Garud Iyengar Garud Iyengar	1878 views, 16:57 DiSCO: Distributed Optimization for Self-Concordant Empirical LossDiSCO: Distributed Optimization for Self-Concordant Empirical Loss Yuchen Zhang Yuchen Zhang 1 comment	2278 views, 16:31 Distributed Box-Constrained Quadratic Optimization for Dual Linear SVMDistributed Box-Constrained Quadratic Optimization for Dual Linear SVM Ching-Pei Lee Ching-Pei Lee	1893 views, 15:50 Adding vs. Averaging in Distributed Primal-Dual OptimizationAdding vs. Averaging in Distributed Primal-Dual Optimization Virginia Smith Virginia Smith
Bayesian Nonparametrics I
1515 views, 18:56 A Bayesian nonparametric procedure for comparing algorithmsA Bayesian nonparametric procedure for comparing algorithms Francesca Mangili Francesca Mangili	1771 views, 17:57 Manifold-valued Dirichlet ProcessesManifold-valued Dirichlet Processes Hyunwoo J. Kim Hyunwoo J. Kim	1515 views, 18:03 JUMP-Means: Small-Variance Asymptotics for Markov Jump ProcessesJUMP-Means: Small-Variance Asymptotics for Markov Jump Processes Jonathan Huggins Jonathan Huggins	1617 views, 17:42 Atomic Spatial ProcessesAtomic Spatial Processes Neil Spencer Neil Spencer	1684 views, 17:37 DP-space: Bayesian Nonparametric Subspace Clustering with Small-variance AsymptoticsDP-space: Bayesian Nonparametric Subspace Clustering with Small-variance Asymptotics Yining Wang Yining Wang
Reinforcement Learning I
2246 views, 19:20 Large-Scale Markov Decision Problems with KL Control Cost and its Application to CrowdsourcingLarge-Scale Markov Decision Problems with KL Control Cost and its ... Alan Malek Alan Malek	1668 views, 15:22 Off-policy Model-based Learning under Unknown Factored DynamicsOff-policy Model-based Learning under Unknown Factored Dynamics Assaf Hallak Assaf Hallak	2286 views, 15:56 A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling BanditsA Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits Pratik Gajane Pratik Gajane	1306 views, 13:33 On TD(0) with function approximation: Concentration bounds and a centered variant with exponential convergenceOn TD(0) with function approximation: Concentration bounds and a centered ... Nathaniel Korda Nathaniel Korda
Learning Theory I
1944 views, 15:19 Entropy-Based Concentration Inequalities for Dependent VariablesEntropy-Based Concentration Inequalities for Dependent Variables Liva Ralaivola Liva Ralaivola	2108 views, 18:27 The Ladder: A Reliable Leaderboard for Machine Learning CompetitionsThe Ladder: A Reliable Leaderboard for Machine Learning Competitions Moritz Hardt Moritz Hardt 1 comment	1888 views, 15:40 Theory of Dual-sparse Regularized Randomized ReductionTheory of Dual-sparse Regularized Randomized Reduction Tianbao Yang Tianbao Yang	1766 views, 15:07 A Theoretical Analysis of Metric Hypothesis Transfer LearningA Theoretical Analysis of Metric Hypothesis Transfer Learning Michaël Perrot Michaël Perrot	1885 views, 15:19 Optimizing Non-decomposable Performance Measures: A Tale of Two ClassesOptimizing Non-decomposable Performance Measures: A Tale of Two Classes Harikrishna Narasimhan Harikrishna Narasimhan
Supervised Learning I
1904 views, 18:48 Learning from Corrupted Binary Labels via Class-Probability EstimationLearning from Corrupted Binary Labels via Class-Probability Estimation Aditya Menon Aditya Menon	2334 views, 17:00 Multi-instance multi-label learning in the presence of novel class instancesMulti-instance multi-label learning in the presence of novel class instances Raviv Raich Raviv Raich	1473 views, 18:43 Entropy evaluation based on confidence intervals of frequency estimates: Application to the learning of decision treesEntropy evaluation based on confidence intervals of frequency estimates: Application ... Mathieu Serrurier Mathieu Serrurier	2425 views, 13:08 Support Matrix MachinesSupport Matrix Machines Luo Luo Luo Luo	1836 views, 13:16 Attribute Efficient Linear Regression with Distribution-Dependent SamplingAttribute Efficient Linear Regression with Distribution-Dependent Sampling Doron Kukliansky Doron Kukliansky
Bandit Learning
1699 views, 19:06 Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple PlaysOptimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit ... Junpei Komiyama Junpei Komiyama	2046 views, 15:08 Simple regret for infinitely many armed banditsSimple regret for infinitely many armed bandits Alexandra Carpentier Alexandra Carpentier	1522 views, 18:06 Efficient Learning in Large-Scale Combinatorial Semi-BanditsEfficient Learning in Large-Scale Combinatorial Semi-Bandits Branislav Kveton Branislav Kveton	1707 views, 23:31 Cascading Bandits: Learning to Rank in the Cascade Model Cascading Bandits: Learning to Rank in the Cascade Model Branislav Kveton Branislav Kveton	1466 views, 19:07 Cheap BanditsCheap Bandits Manjesh Kumar Hanawal Manjesh Kumar Hanawal
1411 views, 22:33 Qualitative Multi-Armed Bandits: A Quantile-Based ApproachQualitative Multi-Armed Bandits: A Quantile-Based Approach Szörényi Balázs Szörényi Balázs
Deep Learning Computations
1795 views, 17:37 Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher MatrixScaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher ... Roger Grosse Roger Grosse	3159 views, 12:53 Compressing Neural Networks with the Hashing TrickCompressing Neural Networks with the Hashing Trick Kilian Q. Weinberger Kilian Q. Weinberger	5870 views, 16:37 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ... Sergey Ioffe Sergey Ioffe	2230 views, 18:20 Optimizing Neural Networks with Kronecker-factored Approximate CurvatureOptimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens James Martens	2926 views, 18:05 Deep Learning with Limited Numerical PrecisionDeep Learning with Limited Numerical Precision Suyog Gupta Suyog Gupta
Causality
2339 views, 17:59 Removing systematic errors for exoplanet search via latent causesRemoving systematic errors for exoplanet search via latent causes Bernhard Schölkopf Bernhard Schölkopf	2046 views, 17:38 Towards a Learning Theory of Cause-Effect InferenceTowards a Learning Theory of Cause-Effect Inference Krikamol Muandet Krikamol Muandet	1680 views, 17:07 Counterfactual Risk Minimization: Learning from Logged Bandit FeedbackCounterfactual Risk Minimization: Learning from Logged Bandit Feedback Adith Swaminathan Adith Swaminathan	1805 views, 16:23 Telling cause from effect in deterministic linear dynamical systemsTelling cause from effect in deterministic linear dynamical systems Naji Shajarisales Naji Shajarisales	1620 views, 17:11 Causal Inference by Identification of Vector Autoregressive Processes with Hidden ComponentsCausal Inference by Identification of Vector Autoregressive Processes with Hidden ... Philipp Geiger Philipp Geiger
1725 views, 17:16 Discovering Temporal Causal Relations from Subsampled DataDiscovering Temporal Causal Relations from Subsampled Data Kun Zhang Kun Zhang
Matrix Factorization
2009 views, 17:48 Guaranteed Tensor Decomposition: A Moment ApproachGuaranteed Tensor Decomposition: A Moment Approach Gongguo Tang Gongguo Tang	2247 views, 17:58 PU Learning for Matrix CompletionPU Learning for Matrix Completion Cho-Jui Hsieh Cho-Jui Hsieh	2048 views, 18:18 Low-Rank Matrix Recovery from Row-and-Column Affine MeasurementsLow-Rank Matrix Recovery from Row-and-Column Affine Measurements Avishai Wagner Avishai Wagner	2108 views, 20:36 Intersecting Faces: Non-negative Matrix Factorization With New GuaranteesIntersecting Faces: Non-negative Matrix Factorization With New Guarantees James Y. Zou James Y. Zou	1809 views, 10:12 CUR Algorithm for Partially Observed MatricesCUR Algorithm for Partially Observed Matrices Miao Xu Miao Xu
1878 views, 18:16 An Explicit Sampling Dependent Spectral Error Bound for Column Subset SelectionAn Explicit Sampling Dependent Spectral Error Bound for Column Subset ... Tianbao Yang Tianbao Yang 1 comment
Sparsity I
1872 views, 21:29 Swept Approximate Message Passing for Sparse EstimationSwept Approximate Message Passing for Sparse Estimation Eric W. Tramel Eric W. Tramel 1 comment	1975 views, 17:32 Towards a Lower Sample Complexity for Robust One-bit Compressed SensingTowards a Lower Sample Complexity for Robust One-bit Compressed Sensing Rongda Zhu Rongda Zhu	2163 views, 20:24 Sparse Subspace Clustering with Missing EntriesSparse Subspace Clustering with Missing Entries René Vidal René Vidal	1685 views, 16:47 Safe Subspace Screening for Nuclear Norm Regularized Least Squares ProblemsSafe Subspace Screening for Nuclear Norm Regularized Least Squares Problems Qiang Zhou Qiang Zhou	2183 views, 20:50 Complete Dictionary Recovery Using Nonconvex OptimizationComplete Dictionary Recovery Using Nonconvex Optimization John Wright John Wright
Ranking Learning
1725 views, 16:58 Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the TopRanking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament ... Arun Rajkumar Arun Rajkumar	1561 views, 18:09 MRA-based Statistical Learning from Incomplete RankingsMRA-based Statistical Learning from Incomplete Rankings Eric Sibony Eric Sibony	15:08 Preference Completion: Large-scale Collaborative Ranking from Pairwise ComparisonsPreference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons	1442 views, 15:28 Distributional Rank Aggregation, and an Axiomatic AnalysisDistributional Rank Aggregation, and an Axiomatic Analysis Harsh Pareek Harsh Pareek	2059 views, 19:07 Spectral MLE: Top-K Rank Aggregation from Pairwise ComparisonsSpectral MLE: Top-K Rank Aggregation from Pairwise Comparisons Changho Suh Changho Suh
1735 views, 14:44 Generalization error bounds for learning to rank: Does the length of document lists matter?Generalization error bounds for learning to rank: Does the length ... Sougata Chaudhuri Sougata Chaudhuri
Optimization I
1952 views, 17:30 A Lower Bound for the Optimization of Finite SumsA Lower Bound for the Optimization of Finite Sums Alekh Agarwal Alekh Agarwal	2177 views, 15:35 Stochastic Optimization with Importance Sampling for Regularized Loss MinimizationStochastic Optimization with Importance Sampling for Regularized Loss Minimization Peilin Zhao Peilin Zhao	1748 views, 15:59 Stochastic Dual Coordinate Ascent with Adaptive ProbabilitiesStochastic Dual Coordinate Ascent with Adaptive Probabilities Zheng Qu Zheng Qu	1969 views, 17:26 Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix ProblemsGlobal Convergence of Stochastic Gradient Descent for Some Non-convex Matrix ... Christopher De Sa Christopher De Sa
Structured Prediction I
1740 views, 19:16 How Hard is Inference for Structured Prediction?How Hard is Inference for Structured Prediction? David Sontag David Sontag	2077 views, 18:22 Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFsPaired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs Stephen Bach Stephen Bach 2 comments	1692 views, 18:19 Learning Submodular Losses with the Lovasz HingeLearning Submodular Losses with the Lovasz Hinge Jiaqian Yu Jiaqian Yu	1582 views, 18:26 PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count dataPeakSeg: constrained optimal segmentation and supervised penalty learning for peak ... Toby Dylan Hocking Toby Dylan Hocking
Reinforcement Learning II
1194 views, 18:23 Non-Stationary Approximate Modified Policy IterationNon-Stationary Approximate Modified Policy Iteration Bruno Scherrer Bruno Scherrer	2775 views, 16:51 Trust Region Policy OptimizationTrust Region Policy Optimization John Schulman John Schulman	1919 views, 17:29 Improved Regret Bounds for Undiscounted Continuous Reinforcement LearningImproved Regret Bounds for Undiscounted Continuous Reinforcement Learning Ronald Ortner Ronald Ortner	1299 views, 17:23 Approximate Dynamic Programming for Two-Player Zero-Sum Markov GamesApproximate Dynamic Programming for Two-Player Zero-Sum Markov Games Julien Pérolat Julien Pérolat
Gaussian Processes I
2182 views, 19:13 Fast Kronecker Inference in Gaussian Processes with non-Gaussian LikelihoodsFast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods Seth Flaxman Seth Flaxman	2212 views, 18:59 A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big DataA Unifying Framework of Anytime Sparse Gaussian Process Regression Models ... Bryan Kian Hsiang Low Bryan Kian Hsiang Low	2013 views, 18:57 Controversy in mechanistic modelling with Gaussian processesControversy in mechanistic modelling with Gaussian processes Benn Macdonald, Dirk Husmeier Benn Macdonald, Dirk Husmeier	4830 views, 17:06 Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP) Andrew Gordon Wilson Andrew Gordon Wilson
Transfer Learning I
1522 views, 18:02 Active Nearest Neighbors in Changing EnvironmentsActive Nearest Neighbors in Changing Environments Christopher Berlind Christopher Berlind	2511 views, 18:18 Asymmetric Transfer Learning with Deep Gaussian ProcessesAsymmetric Transfer Learning with Deep Gaussian Processes Melih Kandemir Melih Kandemir	3075 views, 16:34 An embarrassingly simple approach to zero-shot learningAn embarrassingly simple approach to zero-shot learning Bernardino Romera-Paredes Bernardino Romera-Paredes	1724 views, 14:45 Safe Screening for Multi-Task Feature Learning with Multiple Data MatricesSafe Screening for Multi-Task Feature Learning with Multiple Data Matrices Tianbao Yang Tianbao Yang
Networks and Graphs I
1953 views, 16:58 A Divide and Conquer Framework for Distributed Graph ClusteringLearning with Multiple Data MatricesA Divide and Conquer Framework for Distributed Graph ClusteringLearning with ... Wenzhuo Yang Wenzhuo Yang	1594 views, 12:12 Scalable Model Selection for Large-Scale Factorial Relational ModelsScalable Model Selection for Large-Scale Factorial Relational Models Lu Feng Lu Feng	1963 views, 19:17 Consistent estimation of dynamic and multi-layer block modelsConsistent estimation of dynamic and multi-layer block models Kevin Shuai Xu Kevin Shuai Xu	2124 views, 19:07 Community Detection Using Time-Dependent Personalized PageRankCommunity Detection Using Time-Dependent Personalized PageRank Haim Avron Haim Avron
Deep Learning II
1705 views, 18:04 Variational Generative Stochastic Networks with Collaborative ShapingVariational Generative Stochastic Networks with Collaborative Shaping Philip Bachman Philip Bachman	2099 views, 15:28 How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?How Can Deep Rectifier Networks Achieve Linear Separability and Preserve ... Senjian An Senjian An	3116 views, 16:10 Unsupervised Domain Adaptation by BackpropagationUnsupervised Domain Adaptation by Backpropagation Yaroslav Ganin Yaroslav Ganin	2408 views, 18:24 Learning Transferable Features with Deep Adaptation NetworksLearning Transferable Features with Deep Adaptation Networks Mingsheng Long Mingsheng Long
Networks and Graphs II
1686 views, 18:49 Correlation Clustering in Data StreamsCorrelation Clustering in Data Streams Sudipto Guha Sudipto Guha	1489 views, 17:55 An Aligned Subtree Kernel for Weighted GraphsAn Aligned Subtree Kernel for Weighted Graphs Lu Bai Lu Bai	1899 views, 18:12 HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based CascadesHawkesTopic: A Joint Model for Network Inference and Topic Modeling ... Xinran He Xinran He	1430 views, 14:04 Inferring Graphs from Cascades: A Sparse Recovery FrameworkInferring Graphs from Cascades: A Sparse Recovery Framework Thibaut Horel Thibaut Horel
Online Learning I
1620 views, 12:18 Strongly Adaptive Online LearningStrongly Adaptive Online Learning Alon Gonen Alon Gonen	1495 views, 18:01 Adaptive Belief PropagationAdaptive Belief Propagation Georgios Papachristoudis Georgios Papachristoudis	1667 views, 18:30 The Hedge Algorithm on a ContinuumThe Hedge Algorithm on a Continuum Walid Krichene Walid Krichene
Probabilistic Models I
1598 views, 16:57 Inference in a Partially Observed Queuing Model with Applications in EcologyInference in a Partially Observed Queuing Model with Applications in ... Kevin Winner Kevin Winner	1668 views, 14:16 Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-LikelihoodNon-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood Wenzhao Lian Wenzhao Lian	2237 views, 15:29 On the Relationship between Sum-Product Networks and Bayesian NetworksOn the Relationship between Sum-Product Networks and Bayesian Networks Han Zhao Han Zhao	1833 views, 17:51 Fixed-point algorithms for learning determinantal point processesFixed-point algorithms for learning determinantal point processes Zelda Mariet Zelda Mariet
Learning Theory II
1592 views, 13:19 Convex Calibrated Surrogates for Hierarchical ClassificationConvex Calibrated Surrogates for Hierarchical Classification Harish G. Ramaswamy Harish G. Ramaswamy	1340 views, 17:08 Risk and Regret of Hierarchical Bayesian LearnersRisk and Regret of Hierarchical Bayesian Learners Jonathan Huggins Jonathan Huggins	1991 views, 12:40 Classification with Low Rank and Missing DataClassification with Low Rank and Missing Data Roi Livni Roi Livni	2038 views, 20:14 Surrogate Functions for Maximizing Precision at the TopSurrogate Functions for Maximizing Precision at the Top Purushottam Kar Purushottam Kar
Transfer Learning II
1728 views, 18:46 Non-Linear Cross-Domain Collaborative Filtering via Hyper-Structure TransferNon-Linear Cross-Domain Collaborative Filtering via Hyper-Structure Transfer Shan-Hung Wu Shan-Hung Wu	1598 views, 17:28 A Probabilistic Model for Dirty Multi-task Feature SelectionA Probabilistic Model for Dirty Multi-task Feature Selection Daniel Hernandez-Lobato Daniel Hernandez-Lobato	1369 views, 19:10 Convex Learning of Multiple Tasks and their StructureConvex Learning of Multiple Tasks and their Structure Carlo Ciliberto Carlo Ciliberto	1799 views, 12:42 Convex Formulation for Learning from Positive and Unlabeled DataConvex Formulation for Learning from Positive and Unlabeled Data Marthinus Christoffel du Plessis Marthinus Christoffel du Plessis
Deep Learning and Vision
1452 views, 12:58 Unsupervised Learning of Video Representations using LSTMsUnsupervised Learning of Video Representations using LSTMs Elman Mansimov Elman Mansimov	3252 views, 17:19 Deep Edge-Aware FiltersDeep Edge-Aware Filters Jimmy SJ. Ren Jimmy SJ. Ren	1694 views, 18:25 DRAW: A Recurrent Neural Network For Image GenerationDRAW: A Recurrent Neural Network For Image Generation Karol Gregor Karol Gregor	3537 views, 19:32 Show, Attend and Tell: Neural Image Caption Generation with Visual AttentionShow, Attend and Tell: Neural Image Caption Generation with Visual ... Kelvin Xu Kelvin Xu	2809 views, 17:44 Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural NetworkOnline Tracking by Learning Discriminative Saliency Map with Convolutional Neural ... Seunghoon Hong Seunghoon Hong 1 comment
Bayesian Optimization
1648 views, 18:25 Gradient-based Hyperparameter Optimization through Reversible LearningGradient-based Hyperparameter Optimization through Reversible Learning David Kristjanson Duvenaud David Kristjanson Duvenaud	1801 views, 18:27 Scalable Bayesian Optimization Using Deep Neural NetworksScalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek Jasper Snoek	2359 views, 18:58 High Dimensional Bayesian Optimisation and Bandits via Additive ModelsHigh Dimensional Bayesian Optimisation and Bandits via Additive Models Kirthevasan Kandasamy Kirthevasan Kandasamy	2026 views, 16:35 Safe Exploration for Optimization with Gaussian ProcessesSafe Exploration for Optimization with Gaussian Processes Alkis Gotovos Alkis Gotovos	1431 views, 19:23 Predictive Entropy Search for Bayesian Optimization with Unknown ConstraintsPredictive Entropy Search for Bayesian Optimization with Unknown Constraints José Miguel Hernández-Lobato José Miguel Hernández-Lobato
Variational Inference
1974 views, 17:27 A trust-region method for stochastic variational inference with applications to streaming dataA trust-region method for stochastic variational inference with applications to ... Lucas Theis Lucas Theis	2394 views, 16:13 Variational Inference with Normalizing FlowsVariational Inference with Normalizing Flows Danilo Jimenez Rezende Danilo Jimenez Rezende	2331 views, 18:39 Markov Chain Monte Carlo and Variational Inference: Bridging the GapMarkov Chain Monte Carlo and Variational Inference: Bridging the Gap Tim Salimans Tim Salimans	1573 views, 17:49 An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli ProcessAn Empirical Study of Stochastic Variational Inference Algorithms for the ... Amar Shah Amar Shah	1590 views, 16:40 Scalable Variational Inference in Log-supermodular ModelsScalable Variational Inference in Log-supermodular Models Josip Djolonga Josip Djolonga
Large Scale Learning
1790 views, 16:35 Coresets for Nonparametric Estimation - the Case of DP-MeansCoresets for Nonparametric Estimation - the Case of DP-Means Olivier Bachem Olivier Bachem	1499 views, 15:52 K-hyperplane Hinge-Minimax ClassifierK-hyperplane Hinge-Minimax Classifier Margarita Osadchy Margarita Osadchy	1491 views, 16:51 Faster cover treesFaster cover trees Mike Izbicki Mike Izbicki	2162 views, 13:21 Finding Linear Structure in Large Datasets with Scalable Canonical Correlation AnalysisFinding Linear Structure in Large Datasets with Scalable Canonical Correlation ... Zhuang Ma Zhuang Ma	2272 views, 16:55 Large-scale log-determinant computation through stochastic Chebyshev expansionsLarge-scale log-determinant computation through stochastic Chebyshev expansions Insu Han Insu Han
Structured Prediction II
1718 views, 16:20 Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String PredictionAlgorithms for the Hard Pre-Image Problem of String Kernels and ... Amélie Rolland Amélie Rolland	1415 views, 16:30 Learning Scale-Free Networks by Dynamic Node Specific Degree PriorLearning Scale-Free Networks by Dynamic Node Specific Degree Prior Jinbo Xu Jinbo Xu	3532 views, 18:23 Learning Deep Structured ModelsLearning Deep Structured Models Liang-Chieh Chen Liang-Chieh Chen	2007 views, 16:40 Learning to Search Better than Your TeacherLearning to Search Better than Your Teacher Akshay Krishnamurthy Akshay Krishnamurthy	2091 views, 15:26 Learning Fast-Mixing Models for Structured PredictionLearning Fast-Mixing Models for Structured Prediction Jacob Steinhardt Jacob Steinhardt
Manifold Learning
2002 views, 15:32 Unsupervised Riemannian Metric Learning for Histograms Using Aitchison TransformationsUnsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations Tam Le Tam Le 1 comment	1720 views, 17:13 Learning Local Invariant Mahalanobis DistancesLearning Local Invariant Mahalanobis Distances Ethan Fetaya Ethan Fetaya	1695 views, 16:37 Landmarking Manifolds with Gaussian ProcessesLandmarking Manifolds with Gaussian Processes Dawen Liang Dawen Liang	1501 views, 18:05 Subsampling Methods for Persistent HomologySubsampling Methods for Persistent Homology Bertrand Michel Bertrand Michel	1534 views, 13:34 Bipartite Edge Prediction via Transductive Learning over Product GraphsBipartite Edge Prediction via Transductive Learning over Product Graphs Hanxiao Liu Hanxiao Liu
Gaussian Processes II
2007 views, 16:29 Latent Gaussian Processes for Distribution Estimation of Multivariate Categorical DataLatent Gaussian Processes for Distribution Estimation of Multivariate Categorical Data Yarin Gal Yarin Gal	1559 views, 18:37 Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian ProcessesScalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes Yves-Laurent Kom Samo Yves-Laurent Kom Samo	1595 views, 17:55 Finding Galaxies in the Shadows of Quasars with Gaussian ProcessesFinding Galaxies in the Shadows of Quasars with Gaussian Processes Roman Garnett Roman Garnett
Monte Carlo Methods
1492 views, 16:51 Exponential Integration for Hamiltonian Monte CarloExponential Integration for Hamiltonian Monte Carlo Wei-Lun Chao Wei-Lun Chao	2223 views, 18:39 Nested Sequential Monte Carlo MethodsNested Sequential Monte Carlo Methods Christian Andersson Naesseth Christian Andersson Naesseth	1688 views, 22:19 The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data SubsamplingThe Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive ... Michael Betancourt Michael Betancourt
Hashing
1719 views, 21:27 Binary Embedding: Fundamental Limits and Fast AlgorithmBinary Embedding: Fundamental Limits and Fast Algorithm Constantine Caramanis Constantine Caramanis	1560 views, 10:25 Hashing for Distributed DataHashing for Distributed Data Cong Leng Cong Leng	1566 views, 13:45 On Symmetric and Asymmetric LSHs for Inner Product SearchOn Symmetric and Asymmetric LSHs for Inner Product Search Nathan Srebro Nathan Srebro
Feature Selection I
1882 views, 16:21 Multiview Triplet Embedding: Learning Attributes in Multiple MapsMultiview Triplet Embedding: Learning Attributes in Multiple Maps Ehsan Amid Ehsan Amid	2163 views, 16:32 Low Rank Approximation using Error Correcting Coding MatricesLow Rank Approximation using Error Correcting Coding Matrices Shashanka Ubaru Shashanka Ubaru	1659 views, 20:44 A Unified Framework for Outlier-Robust PCA-like AlgorithmsA Unified Framework for Outlier-Robust PCA-like Algorithms Wenzhuo Yang Wenzhuo Yang
Kernel Methods
1476 views, 18:49 A low variance consistent test of relative dependencyA low variance consistent test of relative dependency Wacha Bounliphone Wacha Bounliphone	1597 views, 16:08 Double Nyström Method: An Efficient and Accurate Nyström Scheme for Large-Scale Data SetsDouble Nyström Method: An Efficient and Accurate Nyström Scheme for ... Woosang Lim Woosang Lim	1711 views, 15:25 The Kendall and Mallows Kernels for PermutationsThe Kendall and Mallows Kernels for Permutations Yunlong Jiao Yunlong Jiao
Computational Advertising and Social Science
1592 views, 17:57 Threshold Influence Model for Allocating Advertising BudgetsThreshold Influence Model for Allocating Advertising Budgets Atsushi Miyauchi Atsushi Miyauchi	3481 views, 18:20 Approval Voting and Incentives in CrowdsourcingApproval Voting and Incentives in Crowdsourcing Nihar B. Shah Nihar B. Shah 2 comments	1692 views, 15:24 Budget Allocation Problem with Multiple Advertisers: A Game Theoretic ViewBudget Allocation Problem with Multiple Advertisers: A Game Theoretic View Akihiro Yabe Akihiro Yabe
Optimization II
2821 views, 16:17 Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random SelectionCoordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random ... Julie Nutini Julie Nutini	1847 views, 18:51 A Stochastic PCA and SVD Algorithm with an Exponential Convergence RateA Stochastic PCA and SVD Algorithm with an Exponential Convergence ... Ohad Shamir Ohad Shamir	1577 views, 19:05 Online Learning of EigenvectorsOnline Learning of Eigenvectors Dan Garber Dan Garber
Approximate Inference I
1684 views, 19:50 A Hybrid Approach for Probabilistic Inference using Random ProjectionsA Hybrid Approach for Probabilistic Inference using Random Projections Stefano Ermon Stefano Ermon	1479 views, 16:40 Reified Context ModelsReified Context Models Jacob Steinhardt Jacob Steinhardt	1477 views, 18:46 Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal LikelihoodRebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood Kohei Hayashi Kohei Hayashi
Bayesian Nonparametrics II
1387 views, 13:00 Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric ModelsOrdered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric ... Mrinal Kanti Das Mrinal Kanti Das	1531 views, 22:52 Bayesian and Empirical Bayesian ForestsBayesian and Empirical Bayesian Forests Matt Taddy Matt Taddy	1202 views, 18:34 Metadata Dependent Mondrian ProcessesMetadata Dependent Mondrian Processes Yi Wang Yi Wang
Time Series Analysis I
3013 views, 16:42 Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal StreamsAccelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams Qi (Rose) Yu Qi (Rose) Yu	2275 views, 15:47 A Multitask Point Process Predictive ModelA Multitask Point Process Predictive Model Wenzhao Lian Wenzhao Lian	1750 views, 18:56 Moderated and Drifting Linear Dynamical SystemsModerated and Drifting Linear Dynamical Systems Jinyan Guan Jinyan Guan
Feature Selection II
1623 views, 17:55 Streaming Sparse Principal Component AnalysisStreaming Sparse Principal Component Analysis Wenzhuo Yang Wenzhuo Yang	1441 views, 14:47 Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCAPushing the Limits of Affine Rank Minimization by Adapting Probabilistic ... Bo Xin Bo Xin	1368 views, 17:48 Statistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-SquaresStatistical and Algorithmic Perspectives on Randomized Sketching for Ordinary Least-Squares Alex Gittens Alex Gittens
Unsupervised Learning I
2107 views, 16:06 Deep Unsupervised Learning using Nonequilibrium ThermodynamicsDeep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Sohl-Dickstein Jascha Sohl-Dickstein	1965 views, 16:09 Structural Maxent ModelsStructural Maxent Models Vitaly Kuznetsov Vitaly Kuznetsov	2140 views, 15:46 Hidden Markov Anomaly DetectionHidden Markov Anomaly Detection Nico Görnitz Nico Görnitz
Optimization III
1532 views, 18:26 Faster Rates for the Frank-Wolfe Method over Strongly-Convex SetsFaster Rates for the Frank-Wolfe Method over Strongly-Convex Sets Dan Garber Dan Garber	1597 views, 18:33 Norm Regularization: Error Bounds and Convergence Rate Analysis of First-Order MethodsNorm Regularization: Error Bounds and Convergence Rate Analysis of First-Order ... Zirui Zhou Zirui Zhou	1658 views, 15:18 Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimizationUn-regularizing: approximate proximal point and faster stochastic algorithms for empirical ... Roy Frostig Roy Frostig
Probabilistic Models II
1546 views, 15:30 Harmonic Exponential Families on ManifoldsHarmonic Exponential Families on Manifolds Taco Cohen Taco Cohen	1407 views, 15:33 Celeste: Variational inference for a generative model of astronomical imagesCeleste: Variational inference for a generative model of astronomical images Jeffrey Regier Jeffrey Regier	1479 views, 20:28 Vector-Space Markov Random Fields via Exponential FamiliesVector-Space Markov Random Fields via Exponential Families Wesley Tansey Wesley Tansey	1379 views, 16:06 Dealing with small data: On the generalization of context treesDealing with small data: On the generalization of context trees Ralf Eggeling Ralf Eggeling
Natural Language Processing I
2207 views, 16:36 Learning Word Representations with Hierarchical Sparse CodingLearning Word Representations with Hierarchical Sparse Coding Dani Yogatama Dani Yogatama	1788 views, 16:58 A Linear Dynamical System Model for TextA Linear Dynamical System Model for Text David Belanger David Belanger	3053 views, 13:26 From Word Embeddings To Document Distances From Word Embeddings To Document Distances Matt J. Kusner Matt J. Kusner	1609 views, 19:05 A Fast Variational Approach for Learning Markov Random Field Language ModelsA Fast Variational Approach for Learning Markov Random Field Language ... Yacine Jernite Yacine Jernite
Submodularity
1895 views, 18:08 On Greedy Maximization of EntropyOn Greedy Maximization of Entropy Dravyansh Sharma Dravyansh Sharma	1901 views, 17:00 Submodularity in Data Subset Selection and Active LearningSubmodularity in Data Subset Selection and Active Learning Kai Wei Kai Wei	2100 views, 19:09 Random Coordinate Descent Methods for Minimizing Decomposable Submodular FunctionsRandom Coordinate Descent Methods for Minimizing Decomposable Submodular Functions Alina Raluca Ene Alina Raluca Ene	1749 views, 18:31 The Power of Randomization: Distributed Submodular Maximization on Massive DatasetsThe Power of Randomization: Distributed Submodular Maximization on Massive Datasets Justin Ward Justin Ward
Online Learning II
1711 views, 17:01 An Online Learning Algorithm for Bilinear ModelsAn Online Learning Algorithm for Bilinear Models Yuanbin Wu Yuanbin Wu	1837 views, 21:47 Online Time Series Prediction with Missing DataOnline Time Series Prediction with Missing Data Oren Anava Oren Anava	1280 views, 21:56 On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy EnvironmentsOn Identifying Good Options under Combinatorially Structured Feedback in Finite ... Yifan Wu Yifan Wu	1267 views, 14:16 Following the Perturbed Leader for Online Structured LearningFollowing the Perturbed Leader for Online Structured Learning Alon Cohen Alon Cohen
Unsupervised Learning II
1769 views, 17:40 Entropic Graph-based Posterior RegularizationEntropic Graph-based Posterior Regularization Maxwell Libbrecht Maxwell Libbrecht	1502 views, 15:25 Information Geometry and Minimum Description Length NetworksInformation Geometry and Minimum Description Length Networks Ke Sun Ke Sun	1449 views, 19:24 Context-based Unsupervised Data Fusion for Decision MakingContext-based Unsupervised Data Fusion for Decision Making Mihaela van der Schaar Mihaela van der Schaar	1797 views, 17:44 Alpha-Beta Divergences Discover Micro and Macro Structures in DataAlpha-Beta Divergences Discover Micro and Macro Structures in Data Sergey Levine Sergey Levine
Deep Learning III
2218 views, 14:40 Weight Uncertainty in Neural NetworkWeight Uncertainty in Neural Network Charles Blundell Charles Blundell	1662 views, 14:06 MADE: Masked Autoencoder for Distribution EstimationMADE: Masked Autoencoder for Distribution Estimation Mathieu Germain Mathieu Germain	1696 views, 11:47 Generative Moment Matching NetworksGenerative Moment Matching Networks Kevin Swersky Kevin Swersky	1790 views, 18:58 Probabilistic Backpropagation for Scalable Learning of Bayesian Neural NetworksProbabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato José Miguel Hernández-Lobato	1770 views, 16:03 Boosted Categorical Restricted Boltzmann Machine for Computational Prediction of Splice JunctionsBoosted Categorical Restricted Boltzmann Machine for Computational Prediction of Splice ... Taehoon Lee Taehoon Lee
Privacy
3014 views, 18:41 Is Feature Selection Secure against Training Data Poisoning?Is Feature Selection Secure against Training Data Poisoning? Battista Biggio Battista Biggio	1692 views, 19:23 Privacy for Free: Posterior Sampling and Stochastic Gradient Monte CarloPrivacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo Yu-Xiang Wang Yu-Xiang Wang	1504 views, 18:43 Rademacher Observations, Private Data, and BoostingRademacher Observations, Private Data, and Boosting Giorgio Patrini Giorgio Patrini	1613 views, 19:33 The Composition Theorem for Differential PrivacyThe Composition Theorem for Differential Privacy Sewoong Oh Sewoong Oh	1625 views, 17:41 Differentially Private Bayesian Optimization Differentially Private Bayesian Optimization Matt J. Kusner Matt J. Kusner
Topic Models
1164 views, 18:19 Markov Mixed Membership ModelsMarkov Mixed Membership Models John Paisley John Paisley	1140 views, 18:02 Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic ModelsLatent Topic Networks: A Versatile Probabilistic Programming Framework for Topic ... James Foulds James Foulds	1270 views, 17:05 Scalable Deep Poisson Factor Analysis for Topic ModelingScalable Deep Poisson Factor Analysis for Topic Modeling David E. Carlson David E. Carlson	949 views, 20:49 Ordinal Mixed Membership ModelsOrdinal Mixed Membership Models Seppo Virtanen Seppo Virtanen	1016 views, 19:03 Efficient Training of LDA on a GPU by Mean-for-Mode EstimationEfficient Training of LDA on a GPU by Mean-for-Mode Estimation Jean-Baptiste Tristan Jean-Baptiste Tristan
Reinforcement Learning III
2740 views, 15:20 Training Deep Convolutional Neural Networks to Play GoTraining Deep Convolutional Neural Networks to Play Go Christopher Clark Christopher Clark 1 comment	1641 views, 18:19 Safe Policy Search for Lifelong Reinforcement Learning with Sublinear RegretSafe Policy Search for Lifelong Reinforcement Learning with Sublinear Regret Eric Eaton Eric Eaton	1530 views, 18:00 Robust partially observable Markov decision processRobust partially observable Markov decision process Takayuki Osogami Takayuki Osogami	3339 views, 15:42 Fictitious Self-Play in Extensive-Form GamesFictitious Self-Play in Extensive-Form Games Johannes Heinrich Johannes Heinrich	1522 views, 16:18 A Deeper Look at Planning as Learning from ReplayA Deeper Look at Planning as Learning from Replay Harm Van Seijen Harm Van Seijen
Gaussian Processes III
1849 views, 19:52 Distributed Gaussian ProcessesDistributed Gaussian Processes Marc Peter Deisenroth Marc Peter Deisenroth	1766 views, 18:03 Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)Enabling scalable stochastic gradient-based inference for Gaussian processes by employing ... Maurizio Filippone Maurizio Filippone	2202 views, 19:04 Improving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty in Frequency InputsImproving the Gaussian Process Sparse Spectrum Approximation by Representing Uncertainty ... Yarin Gal Yarin Gal	1588 views, 19:24 Sparse Variational Inference for Generalized GP ModelsSparse Variational Inference for Generalized GP Models Rishit Sheth Rishit Sheth
Supervised Learning II
1795 views, 15:14 On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition PropertyOn the Optimality of Multi-Label Classification under Subset Zero-One Loss ... Maxime Gasse Maxime Gasse	1555 views, 16:02 Consistent Multiclass Algorithms for Complex Performance MeasuresConsistent Multiclass Algorithms for Complex Performance Measures Harikrishna Narasimhan Harikrishna Narasimhan	1516 views, 17:34 Feature-Budgeted Random ForestFeature-Budgeted Random Forest Feng Nan Feng Nan	1382 views, 16:39 A New Generalized Error Path Algorithm for Model SelectionA New Generalized Error Path Algorithm for Model Selection Bin Gu Bin Gu	1420 views, 12:32 Dynamic Sensing: Better Classification under Acquisition ConstraintsDynamic Sensing: Better Classification under Acquisition Constraints Oran Richman Oran Richman
Reinforcement Learning IV
2056 views, 17:43 Universal Value Function ApproximatorsUniversal Value Function Approximators Tom Schaul Tom Schaul	1557 views, 15:13 High Confidence Policy ImprovementHigh Confidence Policy Improvement Philip S. Thomas Philip S. Thomas	1935 views, 16:21 Abstraction Selection in Model-based Reinforcement LearningAbstraction Selection in Model-based Reinforcement Learning Nan Jiang Nan Jiang 1 comment
Optimization IV
1622 views, 17:12 Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk MinimizationStochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Yuchen Zhang	1888 views, 18:05 Adaptive Stochastic Alternating Direction Method of MultipliersAdaptive Stochastic Alternating Direction Method of Multipliers Peilin Zhao Peilin Zhao	1534 views, 15:39 A General Analysis of the Convergence of ADMMA General Analysis of the Convergence of ADMM Robert Nishihara Robert Nishihara
Bayesian Nonparametrics III
1560 views, 13:58 A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture ModelsA Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models Jimmy Xin Lin Jimmy Xin Lin	1287 views, 17:18 Distributed Inference for Dirichlet Process Mixture Models Distributed Inference for Dirichlet Process Mixture Models Yutian Chen Yutian Chen	1464 views, 17:06 Large-scale Distributed Dependent Nonparametric TreesLarge-scale Distributed Dependent Nonparametric Trees Zhiting Hu Zhiting Hu
Sparsity II
1688 views, 18:18 A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced DataA Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced ... Yining Wang Yining Wang	1690 views, 16:45 Stay on path: PCA along graph pathsStay on path: PCA along graph paths Megasthenis Asteris Megasthenis Asteris	1519 views, 14:36 Geometric Conditions for Subspace-Sparse RecoveryGeometric Conditions for Subspace-Sparse Recovery René Vidal René Vidal
Clustering I
1872 views, 19:40 A Convex Optimization Framework for Bi-ClusteringA Convex Optimization Framework for Bi-Clustering Huan Xu Huan Xu	1950 views, 18:43 Multi-Task Learning for Subspace SegmentationMulti-Task Learning for Subspace Segmentation Yu Wang Yu Wang	1825 views, 16:33 Multi-view Sparse Co-clustering via Proximal Alternating Linearized MinimizationMulti-view Sparse Co-clustering via Proximal Alternating Linearized Minimization Jinbo Bi Jinbo Bi
Vision
1577 views, 16:46 Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVMComplex Event Detection using Semantic Saliency and Nearly-Isotonic SVM Xiaojun Chang Xiaojun Chang	2428 views, 15:30 Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set ClassificationLog-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application ... Bo Xin Bo Xin	1518 views, 17:21 Bayesian Multiple Target LocalizationBayesian Multiple Target Localization Peter I. Frazier Peter I. Frazier
Sparse optimization
2441 views, 17:22 Mind the duality gap: safer rules for the LassoMind the duality gap: safer rules for the Lasso Alexandre Gramfort Alexandre Gramfort	1726 views, 13:56 Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter DomainsTracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter ... Sören Laue Sören Laue	1821 views, 14:50 A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence AnalysisA Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis Jinbo Bi Jinbo Bi
Approximate Inference II
1636 views, 17:35 The Benefits of Learning with Strongly Convex Approximate InferenceThe Benefits of Learning with Strongly Convex Approximate Inference Ben London Ben London 1 comment	1458 views, 16:31 Message Passing for Collective Graphical ModelsMessage Passing for Collective Graphical Models Tao Sun Tao Sun	1564 views, 17:31 Proteins, Particles, and Pseudo-Max-Marginals: A Submodular ApproachProteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach Jason L. Pacheco Jason L. Pacheco
Natural Language Processing II
2264 views, 16:45 Phrase-based Image CaptioningPhrase-based Image Captioning Rémi Lebret Rémi Lebret	1799 views, 13:57 Long Short-Term Memory Over Recursive StructuresLong Short-Term Memory Over Recursive Structures Xiaodan Zhu Xiaodan Zhu	2100 views, 13:41 Bimodal Modelling of Source Code and Natural LanguageBimodal Modelling of Source Code and Natural Language Miltos Allamanis Miltos Allamanis
Time Series Analysis II
1413 views, 18:15 Learning Parametric-Output HMMs with Two Aliased StatesLearning Parametric-Output HMMs with Two Aliased States Roi Weiss Roi Weiss	1891 views, 12:01 Robust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector Autoregressive ProcessesRobust Estimation of Transition Matrices in High Dimensional Heavy-tailed Vector ... Sheng Xu Sheng Xu	2223 views, 20:00 Functional Subspace Clustering with Application to Time SeriesFunctional Subspace Clustering with Application to Time Series Yan Liu Yan Liu
Clustering II
1649 views, 19:39 Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent SpeedupYinyang K-Means: A Drop-In Replacement of the Classic K-Means with ... Xipeng Shen Xipeng Shen	1711 views, 16:28 A Provable Generalized Tensor Spectral Method for Uniform Hypergraph PartitioningA Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning Debarghya Ghoshdastidar Debarghya Ghoshdastidar	1325 views, 12:17 Spectral Clustering via the Power Method - ProvablySpectral Clustering via the Power Method - Provably Alex Gittens Alex Gittens
Learning Theory III
1716 views, 14:43 Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower BoundsDistributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower ... Yuchen Zhang Yuchen Zhang	1790 views, 18:25 Deterministic Independent Component AnalysisDeterministic Independent Component Analysis Csaba Szepesvári Csaba Szepesvári	1527 views, 16:26 Convergence rate of Bayesian tensor estimator and its minimax optimalityConvergence rate of Bayesian tensor estimator and its minimax optimality Taiji Suzuki Taiji Suzuki

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Topic taxonomy

Type of content

Language

Year

ICML 2015 - Lille

32nd International Conference on Machine Learning (ICML), Lille 2015

Tutorials

Welcome Address

Keynote Speakers

Awards

Deep Learning I

Distributed Optimization

Bayesian Nonparametrics I

Reinforcement Learning I

Learning Theory I

Supervised Learning I

Bandit Learning

Deep Learning Computations

Causality

Matrix Factorization

Sparsity I

Ranking Learning

Optimization I

Structured Prediction I

Reinforcement Learning II

Gaussian Processes I

Transfer Learning I

Networks and Graphs I

Deep Learning II

Networks and Graphs II

Online Learning I

Probabilistic Models I

Learning Theory II

Transfer Learning II

Deep Learning and Vision

Bayesian Optimization

Variational Inference

Large Scale Learning

Structured Prediction II

Manifold Learning

Gaussian Processes II

Monte Carlo Methods

Hashing

Feature Selection I

Kernel Methods

Computational Advertising and Social Science

Optimization II

Approximate Inference I

Bayesian Nonparametrics II

Time Series Analysis I

Feature Selection II

Unsupervised Learning I

Optimization III

Probabilistic Models II

Natural Language Processing I

Submodularity

Online Learning II

Unsupervised Learning II

Deep Learning III

Privacy

Topic Models

Reinforcement Learning III

Gaussian Processes III

Supervised Learning II

Reinforcement Learning IV

Optimization IV

Bayesian Nonparametrics III

Sparsity II

Clustering I

Vision

Sparse optimization

Approximate Inference II

Natural Language Processing II

Time Series Analysis II

Clustering II

Learning Theory III

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