| Maxmin q-learning: Controlling the estimation bias of q-learning Q Lan, Y Pan, A Fyshe, M White International Conference on Learning Representations 2020, 2020 | 207 | 2020 |
| Organizing experience: a deeper look at replay mechanisms for sample-based planning in continuous state domains Y Pan, M Zaheer, A White, A Patterson, M White IJCAI, 2018 | 57 | 2018 |
| The In-Sample Softmax for Offline Reinforcement Learning C Xiao, H Wang, Y Pan, A White, M White ICLR 2023, 2023 | 35 | 2023 |
| Accelerated gradient temporal difference learning Y Pan, A White, M White Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 35 | 2017 |
| Greedy Actor-Critic: A New Conditional Cross-Entropy Method for Policy Improvement S Neumann, S Lim, A Joseph, Y Pan, A White, M White ICLR 2023, 2023 | 34* | 2023 |
| Fuzzy tiling activations: A simple approach to learning sparse representations online Y Pan, K Banman, M White ICLR 2022, 2022 | 22 | 2022 |
| Understanding and mitigating the limitations of prioritized experience replay Y Pan, J Mei, A Farahmand, M White, H Yao, M Rohani, J Luo Uncertainty in Artificial Intelligence, 1561-1571, 2022 | 21 | 2022 |
| Reinforcement learning with function-valued action spaces for partial differential equation control Y Pan, A Farahmand, M White, S Nabi, P Grover, D Nikovski International Conference on Machine Learning, 3986-3995, 2018 | 20 | 2018 |
| Hill climbing on value estimates for search-control in Dyna Y Pan, H Yao, A Farahmand, M White IJCAI 2019, 2019 | 19 | 2019 |
| Frequency-based Search-control in Dyna Y Pan, J Mei, A Farahmand ICLR 2020, 2020 | 17 | 2020 |
| Incremental truncated LSTD C Gehring, Y Pan, M White IJCAI 2016, 2016 | 15 | 2016 |
| Effective sketching methods for value function approximation Y Pan, ES Azer, M White Uncertainty in Artificial Intelligence 2017, 2017 | 14 | 2017 |
| Adapting kernel representations online using submodular maximization M Schlegel, Y Pan, J Chen, M White International Conference on Machine Learning, 3037-3046, 2017 | 12 | 2017 |
| Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation Q Lan, Y Pan, J Luo, AR Mahmood Transactions on Machine Learning Research, 2023 | 11* | 2023 |
| An implicit function learning approach for parametric modal regression Y Pan, E Imani, A Farahmand, M White Advances in Neural Information Processing Systems 33, 11442-11452, 2020 | 10 | 2020 |
| An Alternative to Variance: Gini Deviation for Risk-averse Policy Gradient Y Luo, G Liu, P Poupart, Y Pan 2023 Advances in Neural Information Processing Systems (NeurIPS), 2023 | 9 | 2023 |
| An Alternate Policy Gradient Estimator for Softmax Policies S Garg, S Tosatto, Y Pan, M White, AR Mahmood AISTATS 2022, 2021 | 6 | 2021 |
| Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A Ma, Y Pan, A Farahmand Transactions on Machine Learning Research, 2023 | 4 | 2023 |
| Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning X Zhao, Y Pan, C Xiao, S Chandar, J Rajendran UAI 2023, 2023 | 3 | 2023 |
| DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime Z Luo, M Zhu, F Liu, J Li, Y Pan, J Zhou, T Zhu arXiv preprint arXiv:2405.18610, 2024 | 2 | 2024 |
