upper confidence bound

Bayesian optimisation under uncertain inputs AISTATS 2019 Bayesian Optimization Meets Bayesian Optimal Stopping ICML 2019 Bootstrapping Upper Confidence Bound NeurIPS 2019 Bridging the gap between regret minimization and best arm identification, with application to A/B tests AISTATS 2019 Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit IJCAI 2019 Decentralized Cooperative Stochastic Bandits NeurIPS 2019 Learning in Generalized Linear Contextual Bandits with Stochastic Delays NeurIPS 2019 Leveraging Observations in Bandits: Between Risks and Benefits AAAI 2019 Linear Stochastic Bandits Under Safety Constraints NeurIPS 2019 MaxGap Bandit: Adaptive Algorithms for Approximate Ranking NeurIPS 2019 Monte Carlo Tree Search for Policy Optimization IJCAI 2019 Multi-Objective Generalized Linear Bandits IJCAI 2019 Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019 Regret Bounds for Learning State Representations in Reinforcement Learning NeurIPS 2019 Stochastic Bandits with Context Distributions NeurIPS 2019 Top Feasible Arm Identification AISTATS 2019 Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits ICML 2018 A General Approach to Multi-Armed Bandits Under Risk Criteria COLT 2018 Bandit Learning with Positive Externalities NeurIPS 2018 Context-dependent upper-confidence bounds for directed exploration NeurIPS 2018 Contextual Bandits with Stochastic Experts AISTATS 2018 Cost-aware Cascading Bandits IJCAI 2018 Feasible Arm Identification ICML 2018 Information Directed Sampling and Bandits with Heteroscedastic Noise COLT 2018 Profile-Based Bandit with Unknown Profiles JMLR 2018