thompson sampling

Variational Bayesian Optimistic Sampling NeurIPS 2021 Adaptive Exploration in Linear Contextual Bandit AISTATS 2020 Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring NeurIPS 2020 An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles IJCAI 2020 Bandit Algorithms Based on Thompson Sampling for Bounded Reward Distributions ALT 2020 Bayesian Optimization for Categorical and Category-Specific Continuous Inputs AAAI 2020 Diversified Interactive Recommendation with Implicit Feedback AAAI 2020 Federated Bayesian Optimization via Thompson Sampling NeurIPS 2020 Feedback graph regret bounds for Thompson Sampling and UCB ALT 2020 First-Order Bayesian Regret Analysis of Thompson Sampling ALT 2020 Fixed-confidence guarantees for Bayesian best-arm identification AISTATS 2020 Graphical Models Meet Bandits: A Variational Thompson Sampling Approach ICML 2020 Hypermodels for Exploration ICLR 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020 Latent Bandits Revisited NeurIPS 2020 Making Sense of Reinforcement Learning and Probabilistic Inference ICLR 2020 Mixed-Variable Bayesian Optimization IJCAI 2020 Old Dog Learns New Tricks: Randomized UCB for Bandit Problems AISTATS 2020 On Approximate Thompson Sampling with Langevin Algorithms ICML 2020 On Thompson Sampling for Smoother-than-Lipschitz Bandits AISTATS 2020 Random Hypervolume Scalarizations for Provable Multi-Objective Black Box Optimization ICML 2020 Randomized Exploration for Non-Stationary Stochastic Linear Bandits UAI 2020 Randomized Exploration in Generalized Linear Bandits AISTATS 2020 Regret Analysis of Bandit Problems with Causal Background Knowledge UAI 2020 Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling ALT 2020