upper confidence bound

No-regret approximate inference via Bayesian optimisation UAI 2021 Optimizing Conditional Value-At-Risk of Black-Box Functions NeurIPS 2021 Principled Exploration via Optimistic Bootstrapping and Backward Induction ICML 2021 Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions ICML 2021 Regime Switching Bandits NeurIPS 2021 Regulating Greed Over Time in Multi-Armed Bandits JMLR 2021 Reinforcement Learning in Parametric MDPs with Exponential Families AISTATS 2021 Robust Contextual Bandits via Bootstrapping AAAI 2021 Stochastic Bandits with Linear Constraints AISTATS 2021 Stochastic Multi-Armed Bandits with Control Variates NeurIPS 2021 SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning ICML 2021 UCB-based Algorithms for Multinomial Logistic Regression Bandits NeurIPS 2021 UCB Momentum Q-learning: Correcting the bias without forgetting ICML 2021 Value-at-Risk Optimization with Gaussian Processes ICML 2021 Achieving Fairness in the Stochastic Multi-Armed Bandit Problem AAAI 2020 Active Learning of Conditional Mean Embeddings via Bayesian Optimisation UAI 2020 A Farewell to Arms: Sequential Reward Maximization on a Budget with a Giving Up Option AISTATS 2020 Almost Optimal Model-Free Reinforcement Learningvia Reference-Advantage Decomposition NeurIPS 2020 An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles IJCAI 2020 Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions AISTATS 2020 A single algorithm for both restless and rested rotting bandits AISTATS 2020 Bayesian Optimization using Pseudo-Points IJCAI 2020 Constrained Upper Confidence Reinforcement Learning L4DC 2020 Contextual Combinatorial Volatile Multi-armed Bandit with Adaptive Discretization AISTATS 2020 Corruption-Tolerant Gaussian Process Bandit Optimization AISTATS 2020