contextual bandit

PAC-Bayesian Offline Contextual Bandits With Guarantees ICML 2023 Parallel Online Clustering of Bandits via Hedonic Game ICML 2023 Practical Contextual Bandits with Feedback Graphs NeurIPS 2023 Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization NeurIPS 2023 Reinforcement Learning with History Dependent Dynamic Contexts ICML 2023 Representation-Driven Reinforcement Learning ICML 2023 Reward-Biased Maximum Likelihood Estimation for Neural Contextual Bandits: A Distributional Learning Perspective AAAI 2023 Reward Imputation with Sketching for Contextual Batched Bandits NeurIPS 2023 Reward-Mixing MDPs with Few Latent Contexts are Learnable ICML 2023 Risk-aware linear bandits with convex loss AISTATS 2023 Small Total-Cost Constraints in Contextual Bandits with Knapsacks, with Application to Fairness NeurIPS 2023 Stochastic Contextual Bandits with Long Horizon Rewards AAAI 2023 Strategic Apple Tasting NeurIPS 2023 Thompson Sampling for High-Dimensional Sparse Linear Contextual Bandits ICML 2023 Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo AISTATS 2023 Tracking Most Significant Shifts in Nonparametric Contextual Bandits NeurIPS 2023 A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits NeurIPS 2022 Best of Both Worlds Model Selection NeurIPS 2022 Breaking the √T Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits ICML 2022 Causal Contextual Bandits with Targeted Interventions ICLR 2022 Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds NeurIPS 2022 Communication Efficient Distributed Learning for Kernelized Contextual Bandits NeurIPS 2022 Communication Efficient Federated Learning for Generalized Linear Bandits NeurIPS 2022 Conformal Off-Policy Prediction in Contextual Bandits NeurIPS 2022 Congested Bandits: Optimal Routing via Short-term Resets ICML 2022