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, ... (CVPR Oral) Conference on Computer Vision and Pattern Recognition, 2024 | 164 | 2024 |
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 | 90* | 2021 |
Asymptotically efficient off-policy evaluation for tabular reinforcement learning M Yin, YX Wang (AISTATS) International Conference on Artificial Intelligence and Statistics …, 2020 | 78 | 2020 |
Towards instance-optimal offline reinforcement learning with pessimism M Yin, YX Wang (NeurIPS) Advances in neural information processing systems 34, 4065-4078, 2021 | 77 | 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 | 71 | 2022 |
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 | 66 | 2021 |
Theoremqa: A theorem-driven question answering dataset W Chen, M Yin, M Ku, P Lu, Y Wan, X Ma, J Xu, X Wang, T Xia (EMNLP) Empirical Methods in Natural Language Processing, 2023 | 55 | 2023 |
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 | 28 | 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 34, 12890-12903, 2021 | 25 | 2021 |
Offline reinforcement learning with differentiable function approximation is provably efficient M Yin, M Wang, YX Wang (ICLR) Internation Conference on Learning Representations, 2023, 2023 | 14 | 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 | 13 | 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 | 7 | 2023 |
Logarithmic switching cost in reinforcement learning beyond linear mdps D Qiao, M Yin, YX Wang (ISIT) IEEE International Symposium on Information Theory, 2024 | 6 | 2024 |
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 | 6 | 2022 |
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 | 5 | 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 | 4 | 2023 |
No-Regret Linear Bandits beyond Realizability C Liu, M Yin, YX Wang (UAI) The 39th Conference on Uncertainty in Artificial Intelligence, 2023 | 4 | 2023 |
Why quantization improves generalization: Ntk of binary weight neural networks K Zhang, M Yin, YX Wang ICML workshop in Neural Compression, 2023 | 3 | 2023 |
Offline Multitask Representation Learning for Reinforcement Learning H Ishfaq*, T Nguyen-Tang, S Feng, R Arora, M Wang, M Yin*, D Precup* arXiv preprint arXiv:2403.11574, 2024 | 2 | 2024 |
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 | 2 | 2022 |