Learning Theory

Lower bounds on the robustness to adversarial perturbations NeurIPS 2017 Magnitude-Preserving Ranking for Structured Outputs ACML 2017 Maximum Selection and Ranking under Noisy Comparisons ICML 2017 Maxing and Ranking with Few Assumptions NeurIPS 2017 Meritocratic Fairness for Cross-Population Selection ICML 2017 Minimax Estimation of Kernel Mean Embeddings JMLR 2017 Minimax Regret Bounds for Reinforcement Learning ICML 2017 Minimizing a Submodular Function from Samples NeurIPS 2017 Mixing Implies Lower Bounds for Space Bounded Learning COLT 2017 Multi-Objective Non-parametric Sequential Prediction NeurIPS 2017 Multi-Task Learning for Contextual Bandits NeurIPS 2017 Multi-View Decision Processes: The Helper-AI Problem NeurIPS 2017 Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions NeurIPS 2017 Nearly optimal classification for semimetrics JMLR 2017 Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration COLT 2017 Nearly-tight VC-dimension bounds for piecewise linear neural networks COLT 2017 Near Minimax Optimal Players for the Finite-Time 3-Expert Prediction Problem NeurIPS 2017 Neural Networks and Rational Functions ICML 2017 Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks ICML 2017 New bounds on the price of bandit feedback for mistake-bounded online multiclass learning ALT 2017 No Learner Left Behind: On the Complexity of Teaching Multiple Learners Simultaneously IJCAI 2017 Nonparametric Risk Bounds for Time-Series Forecasting JMLR 2017 No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis ICML 2017 On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities COLT 2017 On Learning vs. Refutation COLT 2017