| Quadratically regularized subgradient methods for weakly convex optimization with weakly convex constraints R Ma, Q Lin, T Yang International Conference on Machine Learning, 6554-6564, 2020 | 52* | 2020 |
| Complexity of an inexact proximal-point penalty method for constrained smooth non-convex optimization Q Lin, R Ma, Y Xu Computational optimization and applications 82 (1), 175-224, 2022 | 41 | 2022 |
| Level-set methods for finite-sum constrained convex optimization Q Lin, R Ma, T Yang International conference on machine learning, 3112-3121, 2018 | 34 | 2018 |
| Inexact proximal-point penalty methods for constrained non-convex optimization Q Lin, R Ma, Y Xu arXiv preprint arXiv:1908.11518, 2019 | 33* | 2019 |
| A parameter-free and projection-free restarting level set method for adaptive constrained convex optimization under the error bound condition Q Lin, R Ma, S Nadarajah, N Soheili arXiv preprint arXiv:2010.15267, 2020 | 11 | 2020 |
| First-order methods for convex constrained optimization under error bound conditions with unknown growth parameters Q Lin, R Ma, S Nadarajah, N Soheili arXiv preprint arXiv:2010.15267, 2020 | 2 | 2020 |
| First-order methods for constrained optimization with new iteration complexity and applications in machine learning R Ma The University of Iowa, 2021 | | 2021 |
Qihang LinThe University of IowaCorreu electrònic verificat a uiowa.edu