Zhu, Minghui

14 publications

MLJ 2025 All-Time Safety and Sample-Efficient Meta Update for Online Safe Meta Reinforcement Learning Under Markov Task Transition Zhenyuan Yuan, Siyuan Xu, Minghui Zhu

NeurIPS 2025 Efficient Safe Meta-Reinforcement Learning: Provable Near-Optimality and Anytime Safety Siyuan Xu, Minghui Zhu

NeurIPS 2025 Explainable Reinforcement Learning from Human Feedback to Improve Alignment Shicheng Liu, Siyuan Xu, Wenjie Qiu, Hangfan Zhang, Minghui Zhu

ICML 2025 Meta-Reinforcement Learning with Adaptation from Human Feedback via Preference-Order-Preserving Task Embedding Siyuan Xu, Minghui Zhu

ICLR 2025 UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning Shicheng Liu, Minghui Zhu

NeurIPS 2024 In-Trajectory Inverse Reinforcement Learning: Learn Incrementally Before an Ongoing Trajectory Terminates Shicheng Liu, Minghui Zhu

ICLR 2024 Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis Shicheng Liu, Minghui Zhu

NeurIPS 2024 Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality Under All-Task Optimum Comparator Siyuan Xu, Minghui Zhu

AAAI 2023 Efficient Gradient Approximation Method for Constrained Bilevel Optimization Siyuan Xu, Minghui Zhu

NeurIPS 2023 Learning Multi-Agent Behaviors from Distributed and Streaming Demonstrations Shicheng Liu, Minghui Zhu

NeurIPS 2023 Online Constrained Meta-Learning: Provable Guarantees for Generalization Siyuan Xu, Minghui Zhu

MLJ 2022 An Adaptive Polyak Heavy-Ball Method Samer Saab Jr., Shashi Phoha, Minghui Zhu, Asok Ray

NeurIPS 2022 Byzantine-Tolerant Federated Gaussian Process Regression for Streaming Data Xu Zhang, Zhenyuan Yuan, Minghui Zhu

NeurIPS 2022 Distributed Inverse Constrained Reinforcement Learning for Multi-Agent Systems Shicheng Liu, Minghui Zhu