Learning Theory

Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity AISTATS 2019 Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees NeurIPS 2019 Low-Distortion Social Welfare Functions AAAI 2019 Lower Bounds for Locally Private Estimation via Communication Complexity COLT 2019 Machine Teaching of Active Sequential Learners NeurIPS 2019 Margin-Based Generalization Lower Bounds for Boosted Classifiers NeurIPS 2019 Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards NeurIPS 2019 McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds NeurIPS 2019 Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians ICML 2019 Minimax Learning of Ergodic Markov Chains ALT 2019 Minimax Online Prediction of Varying Bernoulli Process under Variational Approximation ACML 2019 Minimizers of the Empirical Risk and Risk Monotonicity NeurIPS 2019 Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches COLT 2019 Model Consistency for Learning with Mirror-Stratifiable Regularizers AISTATS 2019 Model Selection for Contextual Bandits NeurIPS 2019 Model Selection via the VC Dimension JMLR 2019 Model Similarity Mitigates Test Set Overuse NeurIPS 2019 Multi-Class Learning using Unlabeled Samples: Theory and Algorithm IJCAI 2019 Multi-Element Long Distance Dependencies: Using SPk Languages to Explore the Characteristics of Long-Distance Dependencies ACL 2019 Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits COLT 2019 Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin NeurIPS 2019 Nearly-tight VC-dimension and Pseudodimension Bounds for Piecewise Linear Neural Networks JMLR 2019 New results on information theoretic clustering ICML 2019 Non-Asymptotic Gap-Dependent Regret Bounds for Tabular MDPs NeurIPS 2019 Offline Contextual Bandits with High Probability Fairness Guarantees NeurIPS 2019