| Near-optimal provable uniform convergence in offline policy evaluation for reinforcement learning M Yin, Y Bai, YX Wang (AISTATS oral) International Conference on Artificial Intelligence and …, 2021 | 78* | 2021 |
| Asymptotically efficient off-policy evaluation for tabular reinforcement learning M Yin, YX Wang (AISTATS) International Conference on Artificial Intelligence and Statistics …, 2020 | 65 | 2020 |
| Near-optimal offline reinforcement learning via double variance reduction M Yin, Y Bai, YX Wang (NeurIPS) Advances in neural information processing systems 34, 7677-7688, 2021 | 63 | 2021 |
| Towards instance-optimal offline reinforcement learning with pessimism M Yin, YX Wang (NeurIPS) Advances in neural information processing systems 34, 4065-4078, 2021 | 61 | 2021 |
| Near-optimal offline reinforcement learning with linear representation: Leveraging variance information with pessimism M Yin, Y Duan, M Wang, YX Wang (ICLR) Internation Conference on Learning Representations, 2022, 2022 | 58 | 2022 |
| Optimal uniform ope and model-based offline reinforcement learning in time-homogeneous, reward-free and task-agnostic settings M Yin, YX Wang (NeurIPS) Advances in Neural Information Processing Systems, 2021, 2021 | 22 | 2021 |
| Sample-efficient reinforcement learning with loglog (t) switching cost D Qiao, M Yin, M Min, YX Wang (ICML) International Conference on Machine Learning, 18031-18061, 2022 | 18 | 2022 |
| TheoremQA: A Theorem-driven Question Answering dataset W Chen, M Yin, M Ku, E Wan, X Ma, J Xu, T Xia, X Wang, P Lu (EMNLP) Conference on Empirical Methods in Natural Language Processing, 2023 | 12 | 2023 |
| Offline reinforcement learning with differentiable function approximation is provably efficient M Yin, M Wang, YX Wang (ICLR) Internation Conference on Learning Representations, 2023, 2023 | 11 | 2023 |
| On Instance-Dependent Bounds for Offline Reinforcement Learning with Linear Function Approximation T Nguyen-Tang, M Yin, S Gupta, S Venkatesh, R Arora (AAAI) AAAI Conference on Artificial Intelligence, 2023, 2023 | 10 | 2023 |
| Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality M Yin, W Chen, M Wang, YX Wang (UAI) The 38th Conference on Uncertainty in Artificial Intelligence, 2022 | 4 | 2022 |
| Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPs D Qiao, M Yin, YX Wang arXiv preprint arXiv:2302.12456, 2023 | 3 | 2023 |
| No-Regret Linear Bandits beyond Realizability C Liu, M Yin, YX Wang (UAI) The 39th Conference on Uncertainty in Artificial Intelligence, 2023 | 2 | 2023 |
| Non-stationary Reinforcement Learning under General Function Approximation S Feng, M Yin, R Huang, YX Wang, J Yang, Y Liang (ICML) International Conference on Machine Learning, 2023 | 1 | 2023 |
| Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks K Zhang, M Yin, YX Wang arXiv preprint arXiv:2206.05916, 2022 | 1 | 2022 |
| MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI X Yue, Y Ni, K Zhang, T Zheng, R Liu, G Zhang, S Stevens, D Jiang, ... arXiv preprint arXiv:2311.16502, 2023 | | 2023 |
| Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation M Yin*, NL Kuang*, M Wang, YX Wang, YA Ma (NeurIPS) Advances in neural information processing systems, 2023, 2023 | | 2023 |
| Model-Free Algorithm with Improved Sample Efficiency for Zero-Sum Markov Games S Feng, M Yin, YX Wang, J Yang, Y Liang arXiv preprint arXiv:2308.08858, 2023 | | 2023 |
| Offline Reinforcement Learning with Closed-form Policy Improvement Operators J Li, E Zhang, M Yin, B Qinxun, YX Wang, WY Wang (ICML) International Conference on Machine Learning, 2023 | | 2023 |
| Offline Policy Evaluation for Reinforcement Learning with Adaptively Collected Data S Madhow, D Xiao, M Yin, YX Wang 3rd Offline RL Workshop: Offline RL as a''Launchpad'', 2022 | | 2022 |
Yu-Xiang WangAssociate Professor of Computer Science, UC Santa BarbaraVerified email at cs.ucsb.edu
