Cong Ma
Cited by
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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
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
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
A selective overview of deep learning
J Fan, C Ma, Y Zhong
arXiv preprint arXiv:1904.05526, 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
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
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
Nonconvex matrix factorization from rank-one measurements
Y Li, C Ma, Y Chen, Y Chi
arXiv preprint arXiv:1802.06286, 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
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
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent
T Tong, C Ma, Y Chi
arXiv preprint arXiv:2005.08898, 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
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
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, 2021
Spectral Methods for Data Science: A Statistical Perspective
Y Chen, Y Chi, J Fan, C Ma
arXiv preprint arXiv:2012.08496, 2020
Learning Mixtures of Low-Rank Models
Y Chen, C Ma, HV Poor, Y Chen
arXiv preprint arXiv:2009.11282, 2020
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
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
Minimax Off-Policy Evaluation for Multi-Armed Bandits
C Ma, B Zhu, J Jiao, MJ Wainwright
arXiv preprint arXiv:2101.07781, 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
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