Learning Theory

On Q-learning Convergence for Non-Markov Decision Processes IJCAI 2018 On the Cost Complexity of Crowdsourcing IJCAI 2018 On the Efficiency of Data Collection for Crowdsourced Classification IJCAI 2018 On the Help of Bounded Shot Verifiers, Comparators and Standardisers for Learnability in Inductive Inference ALT 2018 On the Impact of Various Types of Noise on Neural Machine Translation ACL 2018 On the Local Minima of the Empirical Risk NeurIPS 2018 On the Power of Over-parametrization in Neural Networks with Quadratic Activation ICML 2018 On the Practical Computational Power of Finite Precision RNNs for Language Recognition ACL 2018 On the Spectrum of Random Features Maps of High Dimensional Data ICML 2018 On the Statistical Efficiency of Compositional Nonparametric Prediction AISTATS 2018 Open Category Detection with PAC Guarantees ICML 2018 Open Problem: The Dependence of Sample Complexity Lower Bounds on Planning Horizon COLT 2018 Optimal Cooperative Inference AISTATS 2018 Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models COLT 2018 Optimal Quantum Sample Complexity of Learning Algorithms JMLR 2018 Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates NeurIPS 2018 Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate NeurIPS 2018 PAC-Bayes bounds for stable algorithms with instance-dependent priors NeurIPS 2018 PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments CoRL 2018 PAC-learning in the presence of adversaries NeurIPS 2018 Parameterized hardness of active inference PGM 2018 Plug-in Estimators for Conditional Expectations and Probabilities AISTATS 2018 Policy Regret in Repeated Games NeurIPS 2018 Predicting accuracy on large datasets from smaller pilot data ACL 2018 Probability–Revealing Samples AISTATS 2018