upper confidence bound

Dynamic Assortment Optimization with Changing Contextual Information JMLR 2020 Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions L4DC 2020 Feedback graph regret bounds for Thompson Sampling and UCB ALT 2020 From Finite to Countable-Armed Bandits NeurIPS 2020 Generalized Mean Estimation in Monte-Carlo Tree Search IJCAI 2020 Latent Bandits Revisited NeurIPS 2020 Learning to Plan via Deep Optimistic Value Exploration L4DC 2020 Model-Based Reinforcement Learning with Value-Targeted Regression L4DC 2020 Multi-Feedback Bandit Learning with Probabilistic Contexts IJCAI 2020 Neural Contextual Bandits with UCB-based Exploration ICML 2020 Nonmyopic Gaussian Process Optimization with Macro-Actions AISTATS 2020 Old Dog Learns New Tricks: Randomized UCB for Bandit Problems AISTATS 2020 POLY-HOOT: Monte-Carlo Planning in Continuous Space MDPs with Non-Asymptotic Analysis NeurIPS 2020 Private Outsourced Bayesian Optimization ICML 2020 Provable Self-Play Algorithms for Competitive Reinforcement Learning ICML 2020 Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020 Regret Analysis of Bandit Problems with Causal Background Knowledge UAI 2020 Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism ICML 2020 Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack AAAI 2020 Stochastic bandits with arm-dependent delays ICML 2020 The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation ICML 2020 Thompson Sampling for Unsupervised Sequential Selection ACML 2020 Upper Confidence Primal-Dual Reinforcement Learning for CMDP with Adversarial Loss NeurIPS 2020 What You See May Not Be What You Get: UCB Bandit Algorithms Robust to ε-Contamination UAI 2020 AdaLinUCB: Opportunistic Learning for Contextual Bandits IJCAI 2019