Learning Theory

Escaping Local Optima with Non-Elitist Evolutionary Algorithms AAAI 2021 Evaluating model performance under worst-case subpopulations NeurIPS 2021 Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games AAAI 2021 Exact Asymptotics for Linear Quadratic Adaptive Control JMLR 2021 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models ICML 2021 Exact Reduction of Huge Action Spaces in General Reinforcement Learning AAAI 2021 Examining the Inductive Bias of Neural Language Models with Artificial Languages ACL 2021 Experimental Design for Regret Minimization in Linear Bandits AISTATS 2021 Expert advice problem with noisy low rank loss ACML 2021 Exploring Transitivity in Neural NLI Models through Veridicality EACL 2021 Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning NeurIPS 2021 Exponential Lower Bounds for Batch Reinforcement Learning: Batch RL can be Exponentially Harder than Online RL ICML 2021 Exponential savings in agnostic active learning through abstention COLT 2021 Exponential Separation between Two Learning Models and Adversarial Robustness NeurIPS 2021 Exponential Weights Algorithms for Selective Learning COLT 2021 Expressive Power of Invariant and Equivariant Graph Neural Networks ICLR 2021 Extreme Memorization via Scale of Initialization ICLR 2021 Failures of Model-dependent Generalization Bounds for Least-norm Interpolation JMLR 2021 Fast active learning for pure exploration in reinforcement learning ICML 2021 Faster Non-asymptotic Convergence for Double Q-learning NeurIPS 2021 Fast Learning for Renewal Optimization in Online Task Scheduling JMLR 2021 Fast rates for prediction with limited expert advice NeurIPS 2021 Fast Rates for Structured Prediction COLT 2021 Fast Rates for the Regret of Offline Reinforcement Learning COLT 2021 Finding Diverse Trees, Paths, and More AAAI 2021