multi-armed bandit

On the Complexity of Adversarial Decision Making NeurIPS 2022 Open Problem: Finite-Time Instance Dependent Optimality for Stochastic Online Learning with Feedback Graphs COLT 2022 Open Problem: Optimal Best Arm Identification with Fixed-Budget COLT 2022 Optimal Clustering with Noisy Queries via Multi-Armed Bandit ICML 2022 Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits AISTATS 2022 Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams AAAI 2022 Peer Prediction for Learning Agents NeurIPS 2022 Product Ranking for Revenue Maximization with Multiple Purchases NeurIPS 2022 ProtoBandit: Efficient Prototype Selection via Multi-Armed Bandits ACML 2022 Random Effect Bandits AISTATS 2022 Regret, stability & fairness in matching markets with bandit learners AISTATS 2022 Rotting Infinitely Many-Armed Bandits ICML 2022 Safe Exploration for Efficient Policy Evaluation and Comparison ICML 2022 Safety aware changepoint detection for piecewise i.i.d. bandits UAI 2022 Same State, Different Task: Continual Reinforcement Learning without Interference AAAI 2022 Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification AAAI 2022 Scale-Free Adversarial Multi Armed Bandits ALT 2022 Sequential Vaccine Allocation with Delayed Feedback IJCAI 2022 Shielding Federated Learning: Robust Aggregation with Adaptive Client Selection IJCAI 2022 Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model AAAI 2022 Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback ICML 2022 Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity NeurIPS 2022 Solving Multi-Arm Bandit Using a Few Bits of Communication AISTATS 2022 Stochastic Rising Bandits ICML 2022 Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk ICML 2022