Exploration-Exploitation

𝜙-Decoding: Adaptive Foresight Sampling for Balanced Inference-Time Exploration and Exploitation ACL 2025 A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation NeurIPS 2024 Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed Rewards UAI 2024 Convergence of No-Swap-Regret Dynamics in Self-Play NeurIPS 2024 Improving Health Information Access in the World’s Largest Maternal Mobile Health Program via Bandit Algorithms AAAI 2024 Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling ICLR 2024 On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice NeurIPS 2024 Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms NeurIPS 2024 Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health AAAI 2024 Active Coverage for PAC Reinforcement Learning COLT 2023 Allocating Divisible Resources on Arms with Unknown and Random Rewards COLT 2023 A Partially Observable Monte Carlo Planning Algorithm Based on Path Modification ACML 2023 CEM: Constrained Entropy Maximization for Task-Agnostic Safe Exploration AAAI 2023 Efficient Explorative Key-Term Selection Strategies for Conversational Contextual Bandits AAAI 2023 Exploring the Sensitivity of LLMs’ Decision-Making Capabilities: Insights from Prompt Variations and Hyperparameters EMNLP 2023 Fully Dynamic Online Selection through Online Contention Resolution Schemes AAAI 2023 High-dimensional Contextual Bandit Problem without Sparsity NeurIPS 2023 Information-Directed Selection for Top-Two Algorithms COLT 2023 Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration NeurIPS 2023 Multi-Fidelity Multi-Armed Bandits Revisited NeurIPS 2023 On the Sublinear Regret of GP-UCB NeurIPS 2023 Optimistic Whittle Index Policy: Online Learning for Restless Bandits AAAI 2023 Regret Minimization via Saddle Point Optimization NeurIPS 2023 Replicable Bandits ICLR 2023 Stochastic Multi-armed Bandits: Optimal Trade-off among Optimality, Consistency, and Tail Risk NeurIPS 2023