Table of Contents

• Conference on Learning Theory 2015: PrefacePeter Grünwald, Elad Hazan. 1-3 [doi]
• On Consistent Surrogate Risk Minimization and Property ElicitationArpit Agarwal, Shivani Agarwal 0001. 4-22 [doi]
• Online Learning with Feedback Graphs: Beyond BanditsNoga Alon, Nicolò Cesa-Bianchi, Ofer Dekel, Tomer Koren. 23-35 [doi]
• Learning Overcomplete Latent Variable Models through Tensor MethodsAnimashree Anandkumar, Rong Ge, Majid Janzamin. 36-112 [doi]
• Simple, Efficient, and Neural Algorithms for Sparse CodingSanjeev Arora, Rong Ge, Tengyu Ma, Ankur Moitra. 113-149 [doi]
• Label optimal regret bounds for online local learningPranjal Awasthi, Moses Charikar, Kevin A. Lai, Andrej Risteski. 150-166 [doi]
• Efficient Learning of Linear Separators under Bounded NoisePranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner. 167-190 [doi]
• Efficient Representations for Lifelong Learning and AutoencodingMaria-Florina Balcan, Avrim Blum, Santosh Vempala. 191-210 [doi]
• Optimally Combining Classifiers Using Unlabeled DataAkshay Balsubramani, Yoav Freund. 211-225 [doi]
• Minimax Fixed-Design Linear RegressionPeter L. Bartlett, Wouter M. Koolen, Alan Malek, Eiji Takimoto, Manfred K. Warmuth. 226-239 [doi]
• Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex FunctionsAlexandre Belloni, Tengyuan Liang, Hariharan Narayanan, Alexander Rakhlin. 240-265 [doi]
• Bandit Convex Optimization: \(\sqrt{T}\) Regret in One DimensionSébastien Bubeck, Ofer Dekel, Tomer Koren, Yuval Peres. 266-278 [doi]
• The entropic barrier: a simple and optimal universal self-concordant barrierSébastien Bubeck, Ronen Eldan. 279 [doi]
• Optimum Statistical Estimation with Strategic Data SourcesYang Cai, Constantinos Daskalakis, Christos H. Papadimitriou. 280-296 [doi]
• On the Complexity of Learning with KernelsNicolò Cesa-Bianchi, Yishay Mansour, Ohad Shamir. 297-325 [doi]
• Learnability of Solutions to Conjunctive Queries: The Full DichotomyHubie Chen, Matthew Valeriote. 326-337 [doi]
• Sequential Information Maximization: When is Greedy Near-optimal?Yuxin Chen, S. Hamed, Hassani, Amin Karbasi, Andreas Krause. 338-363 [doi]
• Efficient Sampling for Gaussian Graphical Models via Spectral SparsificationDehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng. 364-390 [doi]
• Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recoveryPeter Chin, Anup Rao, Van Vu. 391-423 [doi]
• On-Line Learning Algorithms for Path Experts with Non-Additive LossesCorinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Manfred K. Warmuth. 424-447 [doi]
• Truthful Linear RegressionRachel Cummings, Stratis Ioannidis, Katrina Ligett. 448-483 [doi]
• A PTAS for Agnostically Learning HalfspacesAmit Daniely. 484-502 [doi]
• S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric ClassificationGautam Dasarathy, Robert D. Nowak, Xiaojin Zhu. 503-522 [doi]
• Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix ProblemsYash Deshpande, Andrea Montanari. 523-562 [doi]
• Contextual Dueling BanditsMiroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi. 563-587 [doi]
• Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical ClusteringJustin Eldridge, Mikhail Belkin, Yusu Wang. 588-606 [doi]
• Faster Algorithms for Testing under Conditional SamplingMoein Falahatgar, Ashkan Jafarpour, Alon Orlitsky, Venkatadheeraj Pichapati, Ananda Theertha Suresh. 607-636 [doi]
• Learning and inference in the presence of corrupted inputsUriel Feige, Yishay Mansour, Robert E. Schapire. 637-657 [doi]
• From Averaging to Acceleration, There is Only a Step-sizeNicolas Flammarion, Francis R. Bach. 658-695 [doi]
• Variable Selection is HardDean P. Foster, Howard J. Karloff, Justin Thaler. 696-709 [doi]
• Vector-Valued Property ElicitationRafael M. Frongillo, Ian A. Kash. 710-727 [doi]
• Competing with the Empirical Risk Minimizer in a Single PassRoy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford. 728-763 [doi]
• A Chaining Algorithm for Online Nonparametric RegressionPierre Gaillard, Sébastien Gerchinovitz. 764-796 [doi]
• Escaping From Saddle Points - Online Stochastic Gradient for Tensor DecompositionRong Ge, Furong Huang, Chi Jin, Yang Yuan. 797-842 [doi]
• Learning the dependence structure of rare events: a non-asymptotic studyNicolas Goix, Anne Sabourin, Stéphan Clémençon. 843-860 [doi]
• Thompson Sampling for Learning Parameterized Markov Decision ProcessesAditya Gopalan, Shie Mannor. 861-898 [doi]
• Computational Lower Bounds for Community Detection on Random GraphsBruce E. Hajek, Yihong Wu, Jiaming Xu. 899-928 [doi]
• Adaptive Recovery of Signals by Convex OptimizationZaïd Harchaoui, Anatoli Juditsky, Arkadi Nemirovski, Dmitry Ostrovsky. 929-955 [doi]
• Tensor principal component analysis via sum-of-square proofsSamuel B. Hopkins, Jonathan Shi, David Steurer. 956-1006 [doi]
• Fast Exact Matrix Completion with Finite SamplesPrateek Jain 0002, Praneeth Netrapalli. 1007-1034 [doi]
• Exp-Concavity of Proper Composite LossesParameswaran Kamalaruban, Robert Williamson, Xinhua Zhang. 1035-1065 [doi]
• On Learning Distributions from their SamplesSudeep Kamath, Alon Orlitsky, Dheeraj Pichapati, Ananda Theertha Suresh. 1066-1100 [doi]
• MCMC LearningVarun Kanade, Elchanan Mossel. 1101-1128 [doi]
• Online with Spectral BoundsZohar Shay Karnin, Edo Liberty. 1129-1140 [doi]
• Regret Lower Bound and Optimal Algorithm in Dueling Bandit ProblemJunpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa. 1141-1154 [doi]
• Second-order Quantile Methods for Experts and Combinatorial GamesWouter M. Koolen, Tim van Erven. 1155-1175 [doi]
• Hierarchical Label Queries with Data-Dependent PartitionsSamory Kpotufe, Ruth Urner, Shai Ben-David. 1176-1189 [doi]
• Algorithms for Lipschitz Learning on GraphsRasmus Kyng, Anup Rao, Sushant Sachdeva, Daniel A. Spielman. 1190-1223 [doi]
• Low Rank Matrix Completion with Exponential Family NoiseJean Lafond. 1224-1243 [doi]
• Bad Universal Priors and Notions of OptimalityJan Leike, Marcus Hutter. 1244-1259 [doi]
• Learning with Square Loss: Localization through Offset Rademacher ComplexityTengyuan Liang, Alexander Rakhlin, Karthik Sridharan. 1260-1285 [doi]
• Achieving All with No Parameters: AdaNormalHedgeHaipeng Luo, Robert E. Schapire. 1286-1304 [doi]
• Lower and Upper Bounds on the Generalization of Stochastic Exponentially Concave OptimizationMehrdad Mahdavi, Lijun Zhang 0005, Rong Jin. 1305-1320 [doi]
• Correlation Clustering with Noisy Partial InformationKonstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan. 1321-1342 [doi]
• Online Density Estimation of Bradley-Terry ModelsIssei Matsumoto, Kohei Hatano, Eiji Takimoto. 1343-1359 [doi]
• First-order regret bounds for combinatorial semi-banditsGergely Neu. 1360-1375 [doi]
• Norm-Based Capacity Control in Neural NetworksBehnam Neyshabur, Ryota Tomioka, Nathan Srebro. 1376-1401 [doi]
• Cortical Learning via PredictionChristos H. Papadimitriou, Santosh Vempala. 1402-1422 [doi]
• Partitioning Well-Clustered Graphs: Spectral Clustering Works!Richard Peng, He Sun, Luca Zanetti. 1423-1455 [doi]
• Batched Bandit ProblemsVianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg. 1456 [doi]
• Hierarchies of Relaxations for Online Prediction Problems with Evolving ConstraintsAlexander Rakhlin, Karthik Sridharan. 1457-1479 [doi]
• Fast Mixing for Discrete Point ProcessesPatrick Rebeschini, Amin Karbasi. 1480-1500 [doi]
• Generalized Mixability via Entropic DualityMark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant A. Mehta. 1501-1522 [doi]
• On the Complexity of Bandit Linear OptimizationOhad Shamir. 1523-1551 [doi]
• An Almost Optimal PAC AlgorithmHans-Ulrich Simon. 1552-1563 [doi]
• Minimax rates for memory-bounded sparse linear regressionJacob Steinhardt, John C. Duchi. 1564-1587 [doi]
• Interactive Fingerprinting Codes and the Hardness of Preventing False DiscoveryThomas Steinke, Jonathan Ullman. 1588-1628 [doi]
• Convex Risk Minimization and Conditional Probability EstimationMatus Telgarsky, Miroslav Dudík. 1629-1682 [doi]
• Regularized Linear Regression: A Precise Analysis of the Estimation ErrorChristos Thrampoulidis, Samet Oymak, Babak Hassibi. 1683-1709 [doi]
• Max vs Min: Tensor Decomposition and ICA with nearly Linear Sample ComplexitySantosh Vempala, Ying Xiao. 1710-1723 [doi]
• On Convergence of Emphatic Temporal-Difference LearningH. Yu. 1724-1751 [doi]
• Open Problem: Restricted Eigenvalue Condition for Heavy Tailed DesignsArindam Banerjee, Sheng Chen, Vidyashankar Sivakumar. 1752-1755 [doi]
• Open Problem: The landscape of the loss surfaces of multilayer networksAnna Choromanska, Yann LeCun, Gérard Ben Arous. 1756-1760 [doi]
• Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard SettingsCristobal Guzman. 1761-1763 [doi]
• Open Problem: Online Sabotaged Shortest PathWouter M. Koolen, Manfred K. Warmuth, Dmitry Adamskiy. 1764-1766 [doi]
• Open Problem: Learning Quantum Circuits with QueriesJeremy Kun, Lev Reyzin. 1767-1769 [doi]
• Open Problem: Recursive Teaching Dimension Versus VC DimensionHans-Ulrich Simon, Sandra Zilles. 1770-1772 [doi]