| Efficient approximation of deep relu networks for functions on low dimensional manifolds M Chen, H Jiang, W Liao, T Zhao Advances in neural information processing systems 32, 2019 | 102 | 2019 |
| Differentiable top-k with optimal transport Y Xie, H Dai, M Chen, B Dai, T Zhao, H Zha, W Wei, T Pfister Advances in Neural Information Processing Systems 33, 20520-20531, 2020 | 86 | 2020 |
| Nonparametric regression on low-dimensional manifolds using deep ReLU networks: Function approximation and statistical recovery M Chen, H Jiang, W Liao, T Zhao Information and Inference: A Journal of the IMA 11 (4), 1203-1253, 2022 | 64 | 2022 |
| How important is the train-validation split in meta-learning? Y Bai, M Chen, P Zhou, T Zhao, J Lee, S Kakade, H Wang, C Xiong International Conference on Machine Learning, 543-553, 2021 | 63 | 2021 |
| Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning Q Zhang, M Chen, A Bukharin, P He, Y Cheng, W Chen, T Zhao International Conference on Learning Representations, 2023 | 55 | 2023 |
| Towards understanding the importance of shortcut connections in residual networks T Liu, M Chen, M Zhou, SS Du, E Zhou, T Zhao Advances in neural information processing systems 32, 2019 | 53 | 2019 |
| On generalization bounds of a family of recurrent neural networks M Chen, X Li, T Zhao arXiv preprint arXiv:1910.12947, 2019 | 52 | 2019 |
| Towards understanding hierarchical learning: Benefits of neural representations M Chen, Y Bai, JD Lee, T Zhao, H Wang, C Xiong, R Socher Advances in Neural Information Processing Systems 33, 22134-22145, 2020 | 41 | 2020 |
| On computation and generalization of generative adversarial imitation learning M Chen, Y Wang, T Liu, Z Yang, X Li, Z Wang, T Zhao arXiv preprint arXiv:2001.02792, 2020 | 37 | 2020 |
| Super tickets in pre-trained language models: From model compression to improving generalization C Liang, S Zuo, M Chen, H Jiang, X Liu, P He, T Zhao, W Chen arXiv preprint arXiv:2105.12002, 2021 | 36 | 2021 |
| Distribution approximation and statistical estimation guarantees of generative adversarial networks M Chen, W Liao, H Zha, T Zhao arXiv preprint arXiv:2002.03938, 2020 | 36* | 2020 |
| Large learning rate tames homogeneity: Convergence and balancing effect Y Wang, M Chen, T Zhao, M Tao arXiv preprint arXiv:2110.03677, 2021 | 28 | 2021 |
| On computation and generalization of generative adversarial networks under spectrum control H Jiang, Z Chen, M Chen, F Liu, D Wang, T Zhao International Conference on Learning Representations, 2019 | 28* | 2019 |
| Besov function approximation and binary classification on low-dimensional manifolds using convolutional residual networks H Liu, M Chen, T Zhao, W Liao International Conference on Machine Learning, 6770-6780, 2021 | 25 | 2021 |
| On scalable and efficient computation of large scale optimal transport Y Xie, M Chen, H Jiang, T Zhao, H Zha International Conference on Machine Learning, 6882-6892, 2019 | 22 | 2019 |
| Deep nonparametric estimation of operators between infinite dimensional spaces H Liu, H Yang, M Chen, T Zhao, W Liao arXiv preprint arXiv:2201.00217, 2022 | 16 | 2022 |
| Sample complexity of nonparametric off-policy evaluation on low-dimensional manifolds using deep networks X Ji, M Chen, M Wang, T Zhao arXiv preprint arXiv:2206.02887, 2022 | 14 | 2022 |
| Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data M Chen, K Huang, T Zhao, M Wang arXiv preprint arXiv:2302.07194, 2023 | 12 | 2023 |
| Dimensionality reduction for stationary time series via stochastic nonconvex optimization M Chen, L Yang, M Wang, T Zhao Advances in Neural Information Processing Systems 31, 2018 | 11 | 2018 |
| Benefits of overparameterized convolutional residual networks: Function approximation under smoothness constraint H Liu, M Chen, S Er, W Liao, T Zhang, T Zhao International Conference on Machine Learning, 13669-13703, 2022 | 10 | 2022 |
