Learning Theory

Online Algorithm Selection IJCAI 2017 Online control of the false discovery rate with decaying memory NeurIPS 2017 Online Learning Without Prior Information COLT 2017 Online Learning with Transductive Regret NeurIPS 2017 Online Prediction with Selfish Experts NeurIPS 2017 On Optimal Generalizability in Parametric Learning NeurIPS 2017 On Structured Prediction Theory with Calibrated Convex Surrogate Losses NeurIPS 2017 On the Complexity of Learning from Label Proportions IJCAI 2017 On the Complexity of Learning Neural Networks NeurIPS 2017 On the Consistency of Ordinal Regression Methods JMLR 2017 On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks NeurIPS 2017 On the Learnability of Fully-Connected Neural Networks AISTATS 2017 Open Problem: First-Order Regret Bounds for Contextual Bandits COLT 2017 Open Problem: Meeting Times for Learning Random Automata COLT 2017 Optimal learning via local entropies and sample compression COLT 2017 Optimal Rates for Multi-pass Stochastic Gradient Methods JMLR 2017 Optimal Sample Complexity of M-wise Data for Top-K Ranking NeurIPS 2017 Optimistic posterior sampling for reinforcement learning: worst-case regret bounds NeurIPS 2017 Oracle Complexity of Second-Order Methods for Finite-Sum Problems ICML 2017 PAC Learning Depth-3 AC^0 Circuits of Bounded Top Fanin ALT 2017 Parameter-Free Online Learning via Model Selection NeurIPS 2017 Preference-based Teaching JMLR 2017 Preference-based Teaching of Unions of Geometric Objects ALT 2017 Provably Optimal Algorithms for Generalized Linear Contextual Bandits ICML 2017 Provably Safe Robot Navigation with Obstacle Uncertainty RSS 2017