| 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 | 189* | 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 | 126 | 2019 |
| 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 | 64 | 2019 |
| A selective overview of deep learning J Fan, C Ma, Y Zhong arXiv preprint arXiv:1904.05526, 2019 | 53 | 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 | 50* | 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 | 43 | 2019 |
| 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 | 41 | 2015 |
| Nonconvex matrix factorization from rank-one measurements Y Li, C Ma, Y Chen, Y Chi arXiv preprint arXiv:1802.06286, 2018 | 38 | 2018 |
| 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 | 14 | 2017 |
| Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Y Chen, J Fan, C Ma, Y Yan arXiv preprint arXiv:2001.05484, 2020 | 10 | 2020 |
| Inter-Subject Analysis: A Partial Gaussian Graphical Model Approach C Ma, J Lu, H Liu Journal of the American Statistical Association, 1-57, 2020 | 8* | 2020 |
| Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent T Tong, C Ma, Y Chi arXiv preprint arXiv:2005.08898, 2020 | 8 | 2020 |
| 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 | 4 | 2021 |
| Spectral Methods for Data Science: A Statistical Perspective Y Chen, Y Chi, J Fan, C Ma arXiv preprint arXiv:2012.08496, 2020 | 3 | 2020 |
| Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number T Tong, C Ma, Y Chi arXiv preprint arXiv:2010.13364, 2020 | 3 | 2020 |
| Learning Mixtures of Low-Rank Models Y Chen, C Ma, HV Poor, Y Chen arXiv preprint arXiv:2009.11282, 2020 | 1 | 2020 |
| Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism P Rashidinejad, B Zhu, C Ma, J Jiao, S Russell arXiv preprint arXiv:2103.12021, 2021 | | 2021 |
| Minimax Off-Policy Evaluation for Multi-Armed Bandits C Ma, B Zhu, J Jiao, MJ Wainwright arXiv preprint arXiv:2101.07781, 2021 | | 2021 |
| Comment on “A Tuning-Free Robust and Efficient Approach to High-Dimensional Regression” J Fan, C Ma, K Wang Journal of the American Statistical Association 115 (532), 1720-1725, 2020 | | 2020 |
Yuxin ChenAssistant Professor of Electrical Engineering, Princeton UniversityΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα princeton.edu
