regret bound

Adapting to Misspecification in Contextual Bandits NeurIPS 2020 Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization AAAI 2020 Adaptive Aggregation of Arbitrary Online Trackers with a Regret Bound WACV 2020 Adaptive Discretization for Model-Based Reinforcement Learning NeurIPS 2020 Adaptive Exploration in Linear Contextual Bandit AISTATS 2020 Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm NeurIPS 2020 Adversarial Blocking Bandits NeurIPS 2020 A Farewell to Arms: Sequential Reward Maximization on a Budget with a Giving Up Option AISTATS 2020 A Game-Theoretic Analysis of the Empirical Revenue Maximization Algorithm with Endogenous Sampling NeurIPS 2020 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition NeurIPS 2020 A Low Complexity Algorithm with O(√T) Regret and O(1) Constraint Violations for Online Convex Optimization with Long Term Constraints JMLR 2020 Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring NeurIPS 2020 An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits NeurIPS 2020 A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits AAAI 2020 A new regret analysis for Adam-type algorithms ICML 2020 An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles IJCAI 2020 An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays AISTATS 2020 A Novel Confidence-Based Algorithm for Structured Bandits AISTATS 2020 A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players AISTATS 2020 A single algorithm for both restless and rested rotting bandits AISTATS 2020 A Single Recipe for Online Submodular Maximization with Adversarial or Stochastic Constraints NeurIPS 2020 A Tight Lower Bound and Efficient Reduction for Swap Regret NeurIPS 2020 Bandit Linear Control NeurIPS 2020 Bandits for BMO Functions ICML 2020 Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling L4DC 2020