| Implicit regularization in nonconvex statistical estimation: Gradient descent converges linearly for phase retrieval, matrix completion, and blind deconvolution C Ma, K Wang, Y Chi, Y Chen Foundations of Computational Mathematics, 1-182, 2019 | 270* | 2019 |
| Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval Y Chen, Y Chi, J Fan, C Ma Mathematical Programming 176 (1-2), 5-37, 2019 | 179 | 2019 |
| A selective overview of deep learning J Fan, C Ma, Y Zhong Statistical science: a review journal of the Institute of Mathematical …, 2021 | 109 | 2021 |
| Spectral method and regularized MLE are both optimal for top-K ranking Y Chen, J Fan, C Ma, K Wang Annals of statistics 47 (4), 2204, 2019 | 102 | 2019 |
| Noisy matrix completion: Understanding statistical guarantees for convex relaxation via nonconvex optimization Y Chen, Y Chi, J Fan, C Ma, Y Yan SIAM Journal on Optimization 30 (4), 3098-3121, 2020 | 85* | 2020 |
| Inference and uncertainty quantification for noisy matrix completion Y Chen, J Fan, C Ma, Y Yan Proceedings of the National Academy of Sciences 116 (46), 22931-22937, 2019 | 80 | 2019 |
| Bridging offline reinforcement learning and imitation learning: A tale of pessimism P Rashidinejad, B Zhu, C Ma, J Jiao, S Russell Advances in Neural Information Processing Systems 34, 11702-11716, 2021 | 63 | 2021 |
| Spectral Methods for Data Science: A Statistical Perspective Y Chen, Y Chi, J Fan, C Ma Foundations and Trends® in Machine Learning 14 (5), 566-806, 2021 | 59* | 2021 |
| Panther: Fast top-k similarity search on large networks J Zhang, J Tang, C Ma, H Tong, Y Jing, J Li Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 50 | 2015 |
| Nonconvex matrix factorization from rank-one measurements Y Li, C Ma, Y Chen, Y Chi arXiv preprint arXiv:1802.06286, 2018 | 47 | 2018 |
| Bridging convex and nonconvex optimization in robust PCA: Noise, outliers and missing data Y Chen, J Fan, C Ma, Y Yan The Annals of Statistics 49 (5), 2948-2971, 2021 | 34 | 2021 |
| Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent T Tong, C Ma, Y Chi arXiv preprint arXiv:2005.08898, 2020 | 28 | 2020 |
| Low-rank matrix recovery with scaled subgradient methods: Fast and robust convergence without the condition number T Tong, C Ma, Y Chi IEEE Transactions on Signal Processing 69, 2396-2409, 2021 | 23 | 2021 |
| Fast and Flexible Top-k Similarity Search on Large Networks J Zhang, J Tang, C Ma, H Tong, Y Jing, J Li, W Luyten, MF Moens ACM Transactions on Information Systems (TOIS) 36 (2), 1-30, 2017 | 20 | 2017 |
| Beyond Procrustes: Balancing-free gradient descent for asymmetric low-rank matrix sensing C Ma, Y Li, Y Chi IEEE Transactions on Signal Processing 69, 867-877, 2021 | 19 | 2021 |
| Inter-subject analysis: A partial Gaussian graphical model approach C Ma, J Lu, H Liu Journal of the American Statistical Association, 2021 | 13* | 2021 |
| Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements T Tong, C Ma, A Prater-Bennette, E Tripp, Y Chi arXiv preprint arXiv:2104.14526, 2021 | 12 | 2021 |
| Learning Mixtures of Low-Rank Models Y Chen, C Ma, HV Poor, Y Chen arXiv preprint arXiv:2009.11282, 2020 | 9 | 2020 |
| Jump-Start Reinforcement Learning I Uchendu, T Xiao, Y Lu, B Zhu, M Yan, J Simon, M Bennice, C Fu, C Ma, ... arXiv preprint arXiv:2204.02372, 2022 | 4 | 2022 |
| A new similarity measure for covariate shift with applications to nonparametric regression R Pathak, C Ma, M Wainwright International Conference on Machine Learning, 17517-17530, 2022 | 2 | 2022 |
Yuxin ChenStatistics and Data Science, Wharton School, University of PennsylvaniaVerified email at wharton.upenn.edu
