| An accelerated inexact proximal point method for solving nonconvex-concave min-max problems W Kong, RDC Monteiro SIAM Journal on Optimization 31 (4), 2558-2585, 2021 | 73 | 2021 |
| Complexity of a quadratic penalty accelerated inexact proximal point method for solving linearly constrained nonconvex composite programs W Kong, JG Melo, RDC Monteiro SIAM Journal on Optimization 29 (4), 2566-2593, 2019 | 60 | 2019 |
| A new dog learns old tricks: RL finds classic optimization algorithms W Kong, C Liaw, A Mehta, D Sivakumar International Conference on Learning Representations 7, 2018 | 49 | 2018 |
| Iteration-complexity of an inner accelerated inexact proximal augmented Lagrangian method based on the classical Lagrangian function W Kong, JG Melo, RDC Monteiro SIAM Journal on Optimization 33 (1), 181 - 210, 2023 | 18 | 2023 |
| Iteration complexity of a proximal augmented Lagrangian method for solving nonconvex composite optimization problems with nonlinear convex constraints W Kong, JG Melo, RDC Monteiro Mathematics of Operations Research 48 (2), 1066-1094, 2023 | 16 | 2023 |
| Rankmax: An adaptive projection alternative to the softmax function W Kong, W Krichene, N Mayoraz, S Rendle, L Zhang Advances in Neural Information Processing Systems 33, 633-643, 2020 | 15 | 2020 |
| An efficient adaptive accelerated inexact proximal point method for solving linearly constrained nonconvex composite problems W Kong, JG Melo, RDC Monteiro Computational Optimization and Applications 76, 305-346, 2020 | 14 | 2020 |
| Accelerated Inexact First-Order Methods for Solving Nonconvex Composite Optimization Problems W Kong Georgia Institute of Technology, 2021 | 8 | 2021 |
| Accelerated inexact composite gradient methods for nonconvex spectral optimization problems W Kong, RDC Monteiro Computational Optimization and Applications 82 (3), 673-715, 2022 | 5 | 2022 |
| FISTA and Extensions - Review and New Insights W Kong, JG Melo, RDC Monteiro arXiv preprint arXiv:2107.01267, 2021 | 5 | 2021 |
| An accelerated inexact dampened augmented Lagrangian method for linearly-constrained nonconvex composite optimization problems W Kong, RDC Monteiro Computational Optimization and Applications, 2023 | 4 | 2023 |
| Complexity-optimal and parameter-free first-order methods for finding stationary points of composite optimization problems W Kong arXiv preprint arXiv:2205.13055, 2022 | 2 | 2022 |
| Global Complexity Bound of a Proximal ADMM for Linearly Constrained Nonseparable Nonconvex Composite Programming W Kong, RDC Monteiro SIAM Journal on Optimization 34 (1), 201-224, 2024 | 1 | 2024 |
| DP-Auditorium: a Large Scale Library for Auditing Differential Privacy W Kong, AM Medina, M Ribero, U Syed arXiv preprint arXiv:2307.05608, 2023 | 1* | 2023 |
| A Unified Fast Gradient Clipping Framework for DP-SGD W Kong, AM Medina Thirty-seventh Conference on Neural Information Processing Systems, 2023 | | 2023 |
| DP-SGD for non-decomposable objective functions W Kong, AM Medina, M Ribero arXiv preprint arXiv:2310.03104, 2023 | | 2023 |
| Rankmax: An Adaptive Projection Alternative to the Softmax Function Supplementary Material W Kong, W Krichene, N Mayoraz, S Rendle, L Zhang Advances in Neural Information Processing Systems 33, 633-643, 0 | | |
Renato D C MonteiroProfessor at Georgia TechVerified email at isye.gatech.edu
