Learning Theory

Make the Minority Great Again: First-Order Regret Bound for Contextual Bandits ICML 2018 Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory ICML 2018 Minimax Bounds on Stochastic Batched Convex Optimization COLT 2018 Minimax Estimation of Neural Net Distance NeurIPS 2018 Minimax Rates and Efficient Algorithms for Noisy Sorting ALT 2018 Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning AISTATS 2018 Minimizing Adaptive Regret with One Gradient per Iteration IJCAI 2018 Model-Agnostic Private Learning NeurIPS 2018 Modern Neural Networks Generalize on Small Data Sets NeurIPS 2018 Narrative Schema Stability in News Text COLING 2018 Nearly second-order optimality of online joint detection and estimation via one-sample update schemes AISTATS 2018 Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes NeurIPS 2018 Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes NeurIPS 2018 Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model NeurIPS 2018 Neural Networks for Predicting Algorithm Runtime Distributions IJCAI 2018 Nightmare at test time: How punctuation prevents parsers from generalizing EMNLP 2018 Nonstochastic Bandits with Composite Anonymous Feedback COLT 2018 Normal Bandits of Unknown Means and Variances JMLR 2018 On how complexity affects the stability of a predictor AISTATS 2018 On Learning Markov Chains NeurIPS 2018 On Learning Sparsely Used Dictionaries from Incomplete Samples ICML 2018 Online Learning of Quantum States NeurIPS 2018 Online Learning with Abstention ICML 2018 On Neuronal Capacity NeurIPS 2018 On Oracle-Efficient PAC RL with Rich Observations NeurIPS 2018