regret bound

Open Problem: Model Selection for Contextual Bandits COLT 2020 Optimal Algorithms for Multiplayer Multi-Armed Bandits AISTATS 2020 Optimal Algorithms for Stochastic Multi-Armed Bandits with Heavy Tailed Rewards NeurIPS 2020 Optimal Margin Distribution Learning in Dynamic Environments AAAI 2020 Optimistic Policy Optimization with Bandit Feedback ICML 2020 Optimistic robust linear quadratic dual control L4DC 2020 Parameter-free, Dynamic, and Strongly-Adaptive Online Learning ICML 2020 Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning AAAI 2020 Path Planning Problems with Side Observations—When Colonels Play Hide-and-Seek AAAI 2020 POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis NeurIPS 2020 Prediction with Corrupted Expert Advice NeurIPS 2020 Preselection Bandits ICML 2020 Private Outsourced Bayesian Optimization ICML 2020 Private Reinforcement Learning with PAC and Regret Guarantees ICML 2020 Projection-free Distributed Online Convex Optimization with O(√T) Communication Complexity ICML 2020 Provable Self-Play Algorithms for Competitive Reinforcement Learning ICML 2020 Provably adaptive reinforcement learning in metric spaces NeurIPS 2020 Provably Efficient Exploration in Policy Optimization ICML 2020 Provably Efficient Reinforcement Learning with Kernel and Neural Function Approximations NeurIPS 2020 Provably efficient reinforcement learning with linear function approximation COLT 2020 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020 Randomized Exploration in Generalized Linear Bandits AISTATS 2020 Regret Analysis of Bandit Problems with Causal Background Knowledge UAI 2020 Regret Bound for Safe Gaussian Process Bandit Optimization L4DC 2020 Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems UAI 2020