| Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation? [link] | ICLR 2026 |
| Hao Liang, Jiayu Cheng, Sean R. Sinclair, Yali Du | |
| Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems [link] | 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-last/corresponding authors. | |
| Presented at NeurIPS 2025 Workshop on Efficient Reasoning. | |
| Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds [link] | JMLR |
| Hao Liang, Zhi-Quan Luo | |
| Presented 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 |
| Presented at ICML 2024 Workshop on FoRLaC |
| 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 |