| Preconditioned gradient descent for over-parameterized nonconvex matrix factorization J Zhang, S Fattahi, RY Zhang Advances in Neural Information Processing Systems 34, 5985-5996, 2021 | 33 | 2021 |
| How many samples is a good initial point worth in low-rank matrix recovery? J Zhang, R Zhang Advances in Neural Information Processing Systems 33, 12583-12592, 2020 | 18 | 2020 |
| Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G Zhang, S Fattahi, RY Zhang Journal of Machine Learning Research 24 (163), 1-55, 2023 | 15 | 2023 |
| Weak solution of a doubly degenerate parabolic equation D Kang, T Sangsawang, J Zhang arXiv preprint arXiv:1610.06303, 2016 | 8 | 2016 |
| Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion G Zhang, HM Chiu, RY Zhang Advances in Neural Information Processing Systems 35 (NeurIPS 2022), 2022 | 7 | 2022 |
| Simple alternating minimization provably solves complete dictionary learning G Liang, G Zhang, S Fattahi, RY Zhang arXiv preprint arXiv:2210.12816, 2022 | 4 | 2022 |
| Fast and Minimax Optimal Estimation of Low-Rank Matrices via Non-Convex Gradient Descent. G Zhang, HM Chiu, RY Zhang arXiv preprint arXiv:2305.17224, 2023 | 1 | 2023 |
| Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent G Zhang, HM Chiu, RY Zhang Proceedings of The 27th International Conference on Artificial Intelligence …, 2023 | | 2023 |
| Dynamics and Clustering in Locust Hopper Bands J Zhang | | 2017 |
Richard Y ZhangUniversity of Illinois at Urbana-Champaign在 illinois.edu 的电子邮件经过验证
