| Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence V Charisopoulos, Y Chen, D Davis, M Díaz, L Ding, D Drusvyatskiy Foundations of Computational Mathematics 21 (6), 1505-1593, 2021 | 108 | 2021 |
| Factor group-sparse regularization for efficient low-rank matrix recovery J Fan, L Ding, Y Chen, M Udell Advances in Neural Information Processing Systems 32, 2019 | 88 | 2019 |
| Leave-one-out approach for matrix completion: Primal and dual analysis L Ding, Y Chen IEEE Transactions on Information Theory 66 (11), 7274-7301, 2020 | 86 | 2020 |
| An optimal-storage approach to semidefinite programming using approximate complementarity L Ding, A Yurtsever, V Cevher, JA Tropp, M Udell SIAM Journal on Optimization 31 (4), 2695-2725, 2021 | 43 | 2021 |
| Algorithmic regularization in model-free overparametrized asymmetric matrix factorization L Jiang, Y Chen, L Ding SIAM Journal on Mathematics of Data Science 5 (3), 723-744, 2023 | 32 | 2023 |
| Rank overspecified robust matrix recovery: Subgradient method and exact recovery L Ding, L Jiang, Y Chen, Q Qu, Z Zhu Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 2021 | 28 | 2021 |
| Flat minima generalize for low-rank matrix recovery L Ding, D Drusvyatskiy, M Fazel, Z Harchaoui Information and Inference: A Journal of the IMA 13 (2), iaae009, 2024 | 20 | 2024 |
| Spectral frank-wolfe algorithm: Strict complementarity and linear convergence L Ding, Y Fei, Q Xu, C Yang International conference on machine learning, 2535-2544, 2020 | 19 | 2020 |
| Revisiting spectral bundle methods: Primal-dual (sub) linear convergence rates L Ding, B Grimmer SIAM Journal on Optimization 33 (2), 1305-1332, 2023 | 17 | 2023 |
| On the simplicity and conditioning of low rank semidefinite programs L Ding, M Udell SIAM Journal on Optimization 31 (4), 2614-2637, 2021, 2021 | 13* | 2021 |
| A validation approach to over-parameterized matrix and image recovery L Ding, Z Qin, L Jiang, J Zhou, Z Zhu arXiv preprint arXiv:2209.10675, 2022 | 12 | 2022 |
| Tenips: Inverse propensity sampling for tensor completion C Yang, L Ding, Z Wu, M Udell International Conference on Artificial Intelligence and Statistics, 3160-3168, 2021 | 11 | 2021 |
| FW: A Frank-Wolfe style algorithm with stronger subproblem oracles L Ding, J Fan, M Udell arXiv preprint arXiv:2006.16142, 2020 | 11 | 2020 |
| Frank-wolfe style algorithms for large scale optimization L Ding, M Udell Large-Scale and Distributed Optimization, 215-245, 2018 | 9 | 2018 |
| How over-parameterization slows down gradient descent in matrix sensing: The curses of symmetry and initialization N Xiong, L Ding, SS Du arXiv preprint arXiv:2310.01769, 2023 | 7 | 2023 |
| Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis J Fan, L Ding, C Yang, Z Zhang, M Udell arXiv preprint arXiv:2012.03436, 2020 | 7* | 2020 |
| A strict complementarity approach to error bound and sensitivity of solution of conic programs L Ding, M Udell Optimization Letters 17 (7), 1551-1574, 2023 | 6 | 2023 |
| An overview and comparison of spectral bundle methods for primal and dual semidefinite programs FY Liao, L Ding, Y Zheng arXiv preprint arXiv:2307.07651, 2023 | 5 | 2023 |
| Error bounds, PL condition, and quadratic growth for weakly convex functions, and linear convergences of proximal point methods FY Liao, L Ding, Y Zheng 6th Annual Learning for Dynamics & Control Conference, 993-1005, 2024 | 4 | 2024 |
| Sharpness and well-conditioning of nonsmooth convex formulations in statistical signal recovery L Ding, AL Wang arXiv preprint arXiv:2307.06873, 2023 | 3 | 2023 |
Yudong ChenAssociate Professor, University of Wisconsin-Madison在 wisc.edu 的电子邮件经过验证
