Learning Theory

Representation and Learning of Temporal Relations COLING 2016 Robustness of classifiers: from adversarial to random noise NeurIPS 2016 Sample Complexity of Automated Mechanism Design NeurIPS 2016 Sign rank versus VC dimension COLT 2016 Sparse Nonlinear Regression: Parameter Estimation under Nonconvexity ICML 2016 Stability and Generalization in Structured Prediction JMLR 2016 Statistical-Computational Tradeoffs in Planted Problems and Submatrix Localization with a Growing Number of Clusters and Submatrices JMLR 2016 Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues ICML 2016 Supervised learning through the lens of compression NeurIPS 2016 The Benefit of Multitask Representation Learning JMLR 2016 The Constrained Dantzig Selector with Enhanced Consistency JMLR 2016 The Effect of Combination Functions on the Complexity of Relational Bayesian Networks PGM 2016 The Extended Littlestone’s Dimension for Learning with Mistakes and Abstentions COLT 2016 The Information-Theoretic Requirements of Subspace Clustering with Missing Data ICML 2016 The Limits of Learning with Missing Data NeurIPS 2016 The Optimal Sample Complexity of PAC Learning JMLR 2016 Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning NeurIPS 2016 The Power of Optimization from Samples NeurIPS 2016 The Teaching Dimension of Linear Learners ICML 2016 The Teaching Dimension of Linear Learners JMLR 2016 Tight Complexity Bounds for Optimizing Composite Objectives NeurIPS 2016 Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem COLT 2016 Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers NeurIPS 2016 Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NeurIPS 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016