| Nonconvex robust low-rank matrix recovery X Li, Z Zhu, A Man-Cho So, R Vidal SIAM Journal on Optimization 30 (1), 660-686, 2020 | 90 | 2020 |
| Weakly convex optimization over Stiefel manifold using Riemannian subgradient-type methods X Li, S Chen, Z Deng, Q Qu, Z Zhu, A Man-Cho So SIAM Journal on Optimization 31 (3), 1605-1634, 2021 | 69* | 2021 |
| Dropping symmetry for fast symmetric nonnegative matrix factorization Z Zhu, X Li, K Liu, Q Li Advances in Neural Information Processing Systems 31, 2018 | 46 | 2018 |
| Geometric analysis of nonconvex optimization landscapes for overcomplete learning Q Qu, Y Zhai, X Li, Y Zhang, Z Zhu International Conference on Learning Representations, 2019 | 44* | 2019 |
| Incremental methods for weakly convex optimization X Li, Z Zhu, AMC So, JD Lee arXiv preprint arXiv:1907.11687, 2019 | 37 | 2019 |
| Designing robust sensing matrix for image compression G Li, X Li, S Li, H Bai, Q Jiang, X He IEEE Transactions on Image Processing 24 (12), 5389-5400, 2015 | 36 | 2015 |
| A nonconvex approach for exact and efficient multichannel sparse blind deconvolution Q Qu, X Li, Z Zhu Advances in neural information processing systems 32, 2019 | 35 | 2019 |
| Optimized structured sparse sensing matrices for compressive sensing T Hong, X Li, Z Zhu, Q Li Signal processing 159, 119-129, 2019 | 28 | 2019 |
| Convergence of random reshuffling under the Kurdyka-Lojasiewicz inequality X Li, A Milzarek, J Qiu SIAM Journal on Optimization 33 (2), 1092-1120, 2023 | 24 | 2023 |
| Finding the sparsest vectors in a subspace: Theory, algorithms, and applications Q Qu, Z Zhu, X Li, MC Tsakiris, J Wright, R Vidal arXiv preprint arXiv:2001.06970, 2020 | 19 | 2020 |
| A provable splitting approach for symmetric nonnegative matrix factorization X Li, Z Zhu, Q Li, K Liu IEEE Transactions on Knowledge and Data Engineering 35 (3), 2206-2219, 2021 | 12 | 2021 |
| Distributed random reshuffling over networks K Huang, X Li, A Milzarek, S Pu, J Qiu IEEE Transactions on Signal Processing 71, 1143-1158, 2023 | 10 | 2023 |
| Convergence analysis of alternating nonconvex projections Z Zhu, X Li arXiv preprint arXiv:1802.03889, 2018 | 10 | 2018 |
| A unified convergence theorem for stochastic optimization methods X Li, A Milzarek Advances in Neural Information Processing Systems 35, 33107-33119, 2022 | 9 | 2022 |
| Exact recovery of multichannel sparse blind deconvolution via gradient descent Q Qu, X Li, Z Zhu SIAM Journal on Imaging Sciences 13 (3), 1630-1652, 2020 | 6 | 2020 |
| Nonconvex robust synchronization of rotations H Liu, Z Deng, X Li, S Chen, AMC So Proc. NeurIPS Annu. Workshop Optim. Mach. Learn.(OPT), 1-7, 2020 | 5 | 2020 |
| Revisiting Subgradient Method: Complexity and Convergence Beyond Lipschitz Continuity X Li, L Zhao, D Zhu, AMC So arXiv preprint arXiv:2305.14161, 2023 | 4 | 2023 |
| Distributed stochastic optimization under a general variance condition K Huang, X Li, S Pu arXiv preprint arXiv:2301.12677, 2023 | 4 | 2023 |
| Finite-Time Analysis of Decentralized Single-Timescale Actor-Critic Q Luo, X Li Transactions on Machine Learning Research, 2023 | 2* | 2023 |
| Randomized Coordinate Subgradient Method for Nonsmooth Optimization L Zhao, D Chen, D Zhu, X Li arXiv preprint arXiv:2206.14981, 2022 | 2 | 2022 |
