| Solving random quadratic systems of equations is nearly as easy as solving linear systems Y Chen, EJ Candès Communications on pure and applied mathematics 70 (5), 822-883, 2017 | 672 | 2017 |
| Nonconvex optimization meets low-rank matrix factorization: An overview Y Chi, YM Lu, Y Chen IEEE Transactions on Signal Processing 67 (20), 5239-5269, 2019 | 522 | 2019 |
| 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 20 (3), 451-632, 2020 | 431* | 2020 |
| Robust spectral compressed sensing via structured matrix completion Y Chen, Y Chi IEEE Transactions on Information Theory 60 (10), 6576-6601, 2014 | 366* | 2014 |
| 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 | 292 | 2019 |
| Exact and stable covariance estimation from quadratic sampling via convex programming Y Chen, Y Chi, AJ Goldsmith IEEE Transactions on Information Theory 61 (7), 4034-4059, 2015 | 277 | 2015 |
| 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 | 251* | 2021 |
| Fast global convergence of natural policy gradient methods with entropy regularization S Cen, C Cheng, Y Chen, Y Wei, Y Chi Operations Research 70 (4), 2563-2578, 2022 | 231 | 2022 |
| Compressive two-dimensional harmonic retrieval via atomic norm minimization Y Chi, Y Chen IEEE Transactions on Signal Processing 63 (4), 1030-1042, 2014 | 230 | 2014 |
| 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 | 202* | 2020 |
| Spectral MLE: Top-k rank aggregation from pairwise comparisons Y Chen, C Suh International Conference on Machine Learning, 371-380, 2015 | 187 | 2015 |
| The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled Chi-square P Sur, Y Chen, EJ Candès Probability Theory and Related Fields 175 (1-2), 487-558, 2019 | 182 | 2019 |
| Spectral method and regularized MLE are both optimal for top- ranking Y Chen, J Fan, C Ma, K Wang The Annals of Statistics 47 (4), 2204-2235, 2019 | 171 | 2019 |
| 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 | 170 | 2019 |
| Near-optimal joint object matching via convex relaxation Y Chen, LJ Guibas, QX Huang International Conference on Machine Learning, 2014 | 166 | 2014 |
| Breaking the sample size barrier in model-based reinforcement learning with a generative model G Li, Y Wei, Y Chi, Y Chen Operations Research 72 (1), 203-221, 2024 | 150* | 2024 |
| Sample complexity of asynchronous Q-learning: Sharper analysis and variance reduction G Li, Y Wei, Y Chi, Y Gu, Y Chen IEEE Transactions on Information Theory 68 (1), 448-473, 2022 | 134 | 2022 |
| Communication-efficient distributed optimization in networks with gradient tracking and variance reduction B Li, S Cen, Y Chen, Y Chi Journal of Machine Learning Research 21 (180), 1-51, 2020 | 130 | 2020 |
| Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices H Monajemi, S Jafarpour, M Gavish, DL Donoho, SCME Collaboration Proceedings of the National Academy of Sciences 110 (4), 1181-1186, 2013 | 128 | 2013 |
| Nonconvex low-rank tensor completion from noisy data C Cai, G Li, HV Poor, Y Chen Operations Research 70 (2), 1219-1237, 2022 | 126 | 2022 |
Yuejie ChiCarnegie Mellon Universitycmu.edu의 이메일 확인됨