regret bound

Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits UAI 2020 Geometric Exploration for Online Control NeurIPS 2020 Group-Fair Online Allocation in Continuous Time NeurIPS 2020 Hedging in games: Faster convergence of external and swap regrets NeurIPS 2020 High-Dimensional Sparse Linear Bandits NeurIPS 2020 Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020 Improper Learning for Non-Stochastic Control COLT 2020 Improved Algorithms for Conservative Exploration in Bandits AAAI 2020 Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds NeurIPS 2020 Improved Optimistic Algorithms for Logistic Bandits ICML 2020 Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020 Information Directed Sampling for Linear Partial Monitoring COLT 2020 Kernel Methods for Cooperative Multi-Agent Contextual Bandits ICML 2020 Latent Bandits Revisited NeurIPS 2020 Learning Adversarial Markov Decision Processes with Bandit Feedback and Unknown Transition ICML 2020 Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect UAI 2020 Learning Near Optimal Policies with Low Inherent Bellman Error ICML 2020 Learning to Crawl AAAI 2020 Learning to Play Sequential Games versus Unknown Opponents NeurIPS 2020 Learning with Good Feature Representations in Bandits and in RL with a Generative Model ICML 2020 Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based Algorithms NeurIPS 2020 Linear Bandits with Feature Feedback AAAI 2020 Linear bandits with Stochastic Delayed Feedback ICML 2020 Lipschitz and Comparator-Norm Adaptivity in Online Learning COLT 2020