Han Zhong
Affiliations:- Peking University, Center for Data Science, Beijing, China
According to our database1,
Han Zhong
authored at least 31 papers
between 2020 and 2024.
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Bibliography
2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithm.
CoRR, 2024
Proceedings of the 19th Conference on the Theory of Quantum Computation, 2024
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopically Rational Followers?
J. Mach. Learn. Res., 2023
CoRR, 2023
One Objective to Rule Them All: A Maximization Objective Fusing Estimation and Planning for Exploration.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Posterior Sampling for Competitive RL: Function Approximation and Partial Observation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2022
CoRR, 2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Can Reinforcement Learning Find Stackelberg-Nash Equilibria in General-Sum Markov Games with Myopic Followers?
CoRR, 2021
CoRR, 2021
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Risk-Sensitive Deep RL: Variance-Constrained Actor-Critic Provably Finds Globally Optimal Policy.
CoRR, 2020