| Information-theoretic considerations in batch reinforcement learning J Chen, N Jiang International Conference on Machine Learning, 1042-1051, 2019 | 253 | 2019 |
| Model-free representation learning and exploration in low-rank mdps A Modi*, J Chen*, A Krishnamurthy, N Jiang, A Agarwal arXiv preprint arXiv:2102.07035, 2021 | 52 | 2021 |
| Accelerating nonconvex learning via replica exchange Langevin diffusion Y Chen, J Chen, J Dong, J Peng, Z Wang International Conference on Learning Representations, 2018 | 28 | 2018 |
| Nonstationary reinforcement learning with linear function approximation H Zhou, J Chen, LR Varshney, A Jagmohan Transactions on Machine Learning Research, 2020 | 18 | 2020 |
| Offline reinforcement learning under value and density-ratio realizability: The power of gaps J Chen, N Jiang The 38th Conference on Uncertainty in Artificial Intelligence, 2022 | 14 | 2022 |
| Improved worst-case regret bounds for randomized least-squares value iteration P Agrawal*, J Chen*, N Jiang Proceedings of the AAAI Conference on Artificial Intelligence, 6566--6573, 2021 | 13 | 2021 |
| Towards deployment-efficient reinforcement learning: Lower bound and optimality J Huang, J Chen, L Zhao, T Qin, N Jiang, TY Liu International Conference on Learning Representations, 2022 | 12 | 2022 |
| On the statistical efficiency of reward-free exploration in non-linear RL J Chen*, A Modi*, A Krishnamurthy, N Jiang, A Agarwal Advances in Neural Information Processing Systems, 2022 | 5 | 2022 |
| Reinforcement Learning in Low-Rank MDPs with Density Features A Huang*, J Chen*, N Jiang International Conference on Machine Learning, 2023 | | 2023 |
| Efficient localized inference for large graphical models J Chen, J Peng, Q Liu 27th International Joint Conference on Artificial Intelligence, IJCAI 2018 …, 2018 | | 2018 |
