multi-armed bandit

Cooperative Multi-player Bandit Optimization NeurIPS 2020 Coordination without communication: optimal regret in two players multi-armed bandits COLT 2020 Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality NeurIPS 2020 Delay and Cooperation in Nonstochastic Linear Bandits NeurIPS 2020 Distributed Bandit Learning: Near-Optimal Regret with Efficient Communication ICLR 2020 DORB: Dynamically Optimizing Multiple Rewards with Bandits EMNLP 2020 Efficient Automatic CASH via Rising Bandits AAAI 2020 Efficient Large-Scale Gaussian Process Bandits by Believing only Informative Actions L4DC 2020 Exploration by Optimisation in Partial Monitoring COLT 2020 Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects CoRL 2020 Fatigue-Aware Bandits for Dependent Click Models AAAI 2020 Feedback graph regret bounds for Thompson Sampling and UCB ALT 2020 Fiduciary Bandits ICML 2020 Finding All ε-Good Arms in Stochastic Bandits NeurIPS 2020 Finite Continuum-Armed Bandits NeurIPS 2020 Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 First-Order Bayesian Regret Analysis of Thompson Sampling ALT 2020 Fixed-confidence guarantees for Bayesian best-arm identification AISTATS 2020 From Finite to Countable-Armed Bandits NeurIPS 2020 FrugalML: How to use ML Prediction APIs more accurately and cheaply NeurIPS 2020 Gamification of Pure Exploration for Linear Bandits ICML 2020 Graphical Models Meet Bandits: A Variational Thompson Sampling Approach ICML 2020 Improved Algorithms for Conservative Exploration in Bandits AAAI 2020 Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020