Lijun Ding
Cited by
Cited by
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
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
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
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
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
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
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
Revisiting spectral bundle methods: Primal-dual (sub) linear convergence rates
L Ding, B Grimmer
SIAM Journal on Optimization 33 (2), 1305-1332, 2023
Flat minima generalize for low-rank matrix recovery
L Ding, D Drusvyatskiy, M Fazel, Z Harchaoui
arXiv preprint arXiv:2203.03756, 2022
On the simplicity and conditioning of low rank semidefinite programs
L Ding, M Udell
SIAM Journal on Optimization 31 (4), 2614-2637, 2021, 2021
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
FW: A Frank-Wolfe style algorithm with stronger subproblem oracles
L Ding, J Fan, M Udell
arXiv preprint arXiv:2006.16142, 2020
Frank-wolfe style algorithms for large scale optimization
L Ding, M Udell
Large-Scale and Distributed Optimization, 215-245, 2018
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
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
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
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
Provably convergent policy optimization via metric-aware trust region methods
J Song, N He, L Ding, C Zhao
arXiv preprint arXiv:2306.14133, 2023
Higher-order cone programming
L Ding, LH Lim
arXiv preprint arXiv:1811.05461, 2018
On Squared-Variable Formulations
L Ding, SJ Wright
arXiv preprint arXiv:2310.01784, 2023
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