multi-armed bandit

Competing Bandits in Time Varying Matching Markets L4DC 2023 Competing for Shareable Arms in Multi-Player Multi-Armed Bandits ICML 2023 Complexity Analysis of a Countable-armed Bandit Problem ALT 2023 Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression COLT 2023 Contextual Combinatorial Bandits with Probabilistically Triggered Arms ICML 2023 Contextual Conservative Interleaving Bandits ICML 2023 Covariance-adaptive best arm identification NeurIPS 2023 Decentralized Randomly Distributed Multi-agent Multi-armed Bandit with Heterogeneous Rewards NeurIPS 2023 Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits AAAI 2023 Delayed Bandits: When Do Intermediate Observations Help? ICML 2023 Delayed Feedback in Kernel Bandits ICML 2023 Dimension Reduction in Contextual Online Learning via Nonparametric Variable Selection JMLR 2023 Distributed Differential Privacy in Multi-Armed Bandits ICLR 2023 Doubly Adversarial Federated Bandits ICML 2023 Entropy Regularization for Population Estimation AAAI 2023 Exploiting Correlated Auxiliary Feedback in Parameterized Bandits NeurIPS 2023 Fairness and Welfare Quantification for Regret in Multi-Armed Bandits AAAI 2023 Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms NeurIPS 2023 Finite-Time Logarithmic Bayes Regret Upper Bounds NeurIPS 2023 Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems ALT 2023 Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits AISTATS 2023 Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms NeurIPS 2023 Improved Online Learning Algorithms for CTR Prediction in Ad Auctions ICML 2023 Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data NeurIPS 2023 Improving the Knowledge Gradient Algorithm NeurIPS 2023