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Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning COLT 2025 Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints ICML 2025 Sparsity-Based Interpolation of External, Internal and Swap Regret COLT 2025 Stochastic Online Conformal Prediction with Semi-Bandit Feedback ICML 2025 Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints ICML 2025 Unconstrained Robust Online Convex Optimization ICML 2025 Wait-Less Offline Tuning and Re-solving for Online Decision Making ICML 2025 A General Online Algorithm for Optimizing Complex Performance Metrics ICML 2024 Decoupling Learning and Decision-Making: Breaking the O(√T) Barrier in Online Resource Allocation with First-Order Methods ICML 2024 Designing Decision Support Systems using Counterfactual Prediction Sets ICML 2024 Equilibrium of Data Markets with Externality ICML 2024 Federated Combinatorial Multi-Agent Multi-Armed Bandits ICML 2024 Feel-Good Thompson Sampling for Contextual Dueling Bandits ICML 2024 High-dimensional Linear Bandits with Knapsacks ICML 2024 Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements ICML 2024 Incentivized Learning in Principal-Agent Bandit Games ICML 2024 Information-Directed Pessimism for Offline Reinforcement Learning ICML 2024 Matroid Semi-Bandits in Sublinear Time ICML 2024 Monotone Individual Fairness ICML 2024 Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning ICML 2024 Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints ICML 2024 Online Learning in CMDPs: Handling Stochastic and Adversarial Constraints ICML 2024 Online Learning with Bounded Recall ICML 2024 Online Matrix Completion: A Collaborative Approach with Hott Items ICML 2024 Online Resource Allocation with Non-Stationary Customers ICML 2024