| Almost optimal model-free reinforcement learningvia reference-advantage decomposition Z Zhang, Y Zhou, X Ji Advances in Neural Information Processing Systems 33, 15198-15207, 2020 | 181 | 2020 |
| Is reinforcement learning more difficult than bandits? a near-optimal algorithm escaping the curse of horizon Z Zhang, X Ji, S Du Conference on Learning Theory, 4528-4531, 2021 | 129 | 2021 |
| Regret minimization for reinforcement learning by evaluating the optimal bias function Z Zhang, X Ji Advances in Neural Information Processing Systems 32, 2019 | 86 | 2019 |
| Improved variance-aware confidence sets for linear bandits and linear mixture mdp Z Zhang, J Yang, X Ji, SS Du Advances in Neural Information Processing Systems 34, 4342-4355, 2021 | 69* | 2021 |
| Near optimal reward-free reinforcement learning Z Zhang, S Du, X Ji International Conference on Machine Learning, 12402-12412, 2021 | 62* | 2021 |
| Model-free reinforcement learning: from clipped pseudo-regret to sample complexity Z Zhang, Y Zhou, X Ji International Conference on Machine Learning, 12653-12662, 2021 | 43 | 2021 |
| Horizon-free reinforcement learning in polynomial time: the power of stationary policies Z Zhang, X Ji, S Du Conference on Learning Theory, 3858-3904, 2022 | 29 | 2022 |
| Settling the sample complexity of online reinforcement learning Z Zhang, Y Chen, JD Lee, SS Du The Thirty Seventh Annual Conference on Learning Theory, 5213-5219, 2024 | 24 | 2024 |
| Sharper model-free reinforcement learning for average-reward markov decision processes Z Zhang, Q Xie The Thirty Sixth Annual Conference on Learning Theory, 5476-5477, 2023 | 17 | 2023 |
| Optimal multi-distribution learning Z Zhang, W Zhan, Y Chen, SS Du, JD Lee The Thirty Seventh Annual Conference on Learning Theory, 5220-5223, 2024 | 16 | 2024 |
| Near-optimal regret bounds for multi-batch reinforcement learning Z Zhang, Y Jiang, Y Zhou, X Ji Advances in Neural Information Processing Systems 35, 24586-24596, 2022 | 15 | 2022 |
| Sharp variance-dependent bounds in reinforcement learning: Best of both worlds in stochastic and deterministic environments R Zhou, Z Zihan, SS Du International Conference on Machine Learning, 42878-42914, 2023 | 12 | 2023 |
| Almost optimal batch-regret tradeoff for batch linear contextual bandits Z Zhang, X Ji, Y Zhou arXiv preprint arXiv:2110.08057, 2021 | 9 | 2021 |
| Achieving tractable minimax optimal regret in average reward mdps V Boone, Z Zhang arXiv preprint arXiv:2406.01234, 2024 | 5 | 2024 |
| Horizon-free regret for linear markov decision processes Z Zhang, JD Lee, Y Chen, SS Du arXiv preprint arXiv:2403.10738, 2024 | 3 | 2024 |
| Anytime Acceleration of Gradient Descent Z Zhang, JD Lee, SS Du, Y Chen arXiv preprint arXiv:2411.17668, 2024 | 1 | 2024 |
Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonEmail được xác minh tại cs.washington.edu