Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems | NeurIPS 2025 (Spotlight) |
Hao Liang*, Shuqing Shi*, Yudi Zhang, Biwei Huang, Yali Du | |
Why GRPO Needs Normalization: A Local-Curvature Perspective on Adaptive Gradients | To appear |
Cheng Ge*, Heqi Yin*, Hao Liang†, Jiawei Zhang† | |
* Equal contribution. † Co-corresponding / equal advising. | |
Scheduled for poster presentation at NeurIPS 2025 Workshop on Efficient Reasoning. | |
Is Pure Exploitation Sufficient for Sequential Decision-Making with Exogenous Information? | To appear |
Hao Liang, Jiayu Cheng, Sean R. Sinclair, Yali Du | |
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds [link] | JMLR |
Hao Liang, Zhi-Quan Luo | |
Scheduled for poster presentation at NeurIPS 2025 (The NeurIPS/ICLR/ICML Journal-to-Conference Track). An earlier version presented at NeurIPS 2021 Workshop on Ecological Theory of RL | |
Bridging Distributional and Risk-Sensitive Reinforcement Learning: Balancing Statistical, Computational, and Risk Considerations [link] |
Hao Liang |
Present at ICML 2024 Workshop on FoRLaC |
An Economic and Low-carbon Dispatch Algorithm for Microgrids with Electric Vehicles | PSET 2024 |
Jiayu Cheng*, Hao Liang*, Xiaoying Tang, Shuguang Cui | |
Under review at IEEE Transactions on Industry Applications (TIA). An earlier version received the best oral presentation award at PSET 2024. | |
Optimistic Thompson Sampling for No-regret Learning in Unknown Games [arXiv] |
Yingru Li, Liangqi Liu, Wenqiang Pu, Hao Liang, Zhi-Quan Luo |
Under review at IEEE Transactions on Signal Processing (TSP) |
Regret Bounds for Risk-sensitive Reinforcement Learning with Lipschitz Dynamic Risk Measures [AISTATS] | AISTATS 2024 |
Hao Liang, Zhi-Quan Luo | |
An earlier version presented at ICML 2023 Workshop on New Frontiers in Learning, Control, and Dynamical Systems | |
A Distribution Optimization Framework for Confidence Bounds of Risk Measures [ICML] | ICML 2023 |
Hao Liang, Zhi-Quan Luo | |
Revisiting Minimax Lower Bounds in Unknown Matrix Game |
Hao Liang, Yingru Li, Zhi-Quan Luo |
A Convergence Analysis of Categorical Distributional Reinforcement Learning Algorithm |
Hao Liang, Zhi-Quan Luo |