| Nearly minimax optimal reinforcement learning with linear function approximation P Hu, Y Chen, L Huang International Conference on Machine Learning, 8971-9019, 2022 | 30 | 2022 |
| Effective multi-user delay-constrained scheduling with deep recurrent reinforcement learning P Hu, L Pan, Y Chen, Z Fang, L Huang Proceedings of the Twenty-Third International Symposium on Theory …, 2022 | 4 | 2022 |
| Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs P Hu, Y Chen, L Huang The Eleventh International Conference on Learning Representations, 2022 | 3 | 2022 |
| Multi-User Delay-Constrained Scheduling With Deep Recurrent Reinforcement Learning P Hu, Y Chen, L Pan, Z Fang, F Xiao, L Huang IEEE/ACM Transactions on Networking, 2024 | 2 | 2024 |
| Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback Y Chen, Y Du, P Hu, S Wang, D Wu, L Huang The Twelfth International Conference on Learning Representations, 2023 | 2* | 2023 |
| Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation Y Chen, X Zhang, S Wang, L Huang arXiv preprint arXiv:2402.18159, 2024 | | 2024 |
| Provably Efficient Partially Observable Risk-Sensitive Reinforcement Learning with Hindsight Observation T Zhang, Y Chen, L Huang arXiv preprint arXiv:2402.18149, 2024 | | 2024 |
