multi-armed bandit

Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization ICML 2021 Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs NeurIPS 2021 Budgeted and Non-Budgeted Causal Bandits AISTATS 2021 Causal Bandits with Unknown Graph Structure NeurIPS 2021 Collaborative Bayesian Optimization with Fair Regret ICML 2021 Combinatorial Blocking Bandits with Stochastic Delays ICML 2021 Combinatorial Pure Exploration with Bottleneck Reward Function NeurIPS 2021 Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback AAAI 2021 Comparison Lift: Bandit-based Experimentation System for Online Advertising AAAI 2021 Confidence-Budget Matching for Sequential Budgeted Learning ICML 2021 Contextual Bandits with Delayed Feedback and Semi-supervised Learning (Student Abstract) AAAI 2021 Contextual Blocking Bandits AISTATS 2021 Continuous Mean-Covariance Bandits NeurIPS 2021 Cooperative and Stochastic Multi-Player Multi-Armed Bandit: Optimal Regret With Neither Communication Nor Collisions COLT 2021 Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback NeurIPS 2021 CORe: Capitalizing On Rewards in Bandit Exploration UAI 2021 Corralling Stochastic Bandit Algorithms AISTATS 2021 DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits AAAI 2021 Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification NeurIPS 2021 DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization IJCAI 2021 Dichotomous Optimistic Search to Quantify Human Perception ICML 2021 Differentially Private Multi-Armed Bandits in the Shuffle Model NeurIPS 2021 Dominate or Delete: Decentralized Competing Bandits in Serial Dictatorship AISTATS 2021 Double Explore-then-Commit: Asymptotic Optimality and Beyond COLT 2021 Doubly Robust Thompson Sampling with Linear Payoffs NeurIPS 2021