| A generic first-order algorithmic framework for bi-level programming beyond lower-level singleton R Liu, P Mu, X Yuan, S Zeng, J Zhang International Conference on Machine Learning, 6305-6315, 2020 | 80 | 2020 |
| Discerning the linear convergence of ADMM for structured convex optimization through the lens of variational analysis X Yuan, S Zeng, J Zhang The Journal of Machine Learning Research 21 (1), 3182-3256, 2020 | 30 | 2020 |
| A value-function-based interior-point method for non-convex bi-level optimization R Liu, X Liu, X Yuan, S Zeng, J Zhang International Conference on Machine Learning, 6882-6892, 2021 | 26 | 2021 |
| Variational analysis perspective on linear convergence of some first order methods for nonsmooth convex optimization problems JJ Ye, X Yuan, S Zeng, J Zhang Set-Valued and Variational Analysis, 1-35, 2021 | 24 | 2021 |
| Towards gradient-based bilevel optimization with non-convex followers and beyond R Liu, Y Liu, S Zeng, J Zhang Advances in Neural Information Processing Systems 34, 8662-8675, 2021 | 23 | 2021 |
| Partial error bound conditions and the linear convergence rate of the alternating direction method of multipliers Y Liu, X Yuan, S Zeng, J Zhang SIAM Journal on Numerical Analysis 56 (4), 2095-2123, 2018 | 22 | 2018 |
| Perturbation techniques for convergence analysis of proximal gradient method and other first-order algorithms via variational analysis X Wang, JJ Ye, X Yuan, S Zeng, J Zhang Set-Valued and Variational Analysis, 1-41, 2021 | 21 | 2021 |
| A general descent aggregation framework for gradient-based bi-level optimization R Liu, P Mu, X Yuan, S Zeng, J Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (1), 38-57, 2022 | 18 | 2022 |
| A globally convergent proximal Newton-type method in nonsmooth convex optimization BS Mordukhovich, X Yuan, S Zeng, J Zhang Mathematical Programming, 1-38, 2022 | 12 | 2022 |
| Difference of convex algorithms for bilevel programs with applications in hyperparameter selection JJ Ye, X Yuan, S Zeng, J Zhang Mathematical Programming, 1-34, 2022 | 10 | 2022 |
| Task-oriented convex bilevel optimization with latent feasibility R Liu, L Ma, X Yuan, S Zeng, J Zhang IEEE Transactions on Image Processing 31, 1190-1203, 2022 | 10* | 2022 |
| Primal–dual hybrid gradient method for distributionally robust optimization problems Y Liu, X Yuan, S Zeng, J Zhang Operations Research Letters 45 (6), 625-630, 2017 | 10 | 2017 |
| Block coordinate proximal gradient method for nonconvex optimization problems: convergence analysis X Wang, X Yuan, S Zeng, J Zhang, J Zhou | 8 | 2018 |
| Value function based difference-of-convex algorithm for bilevel hyperparameter selection problems LL Gao, J Ye, H Yin, S Zeng, J Zhang International Conference on Machine Learning, 7164-7182, 2022 | 4 | 2022 |
| Value-function-based sequential minimization for bi-level optimization R Liu, X Liu, S Zeng, J Zhang, Y Zhang arXiv preprint arXiv:2110.04974, 2021 | 3 | 2021 |
| Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity R Liu, Y Liu, W Yao, S Zeng, J Zhang arXiv preprint arXiv:2302.03407, 2023 | 1 | 2023 |
| Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training R Liu, X Liu, S Zeng, J Zhang, Y Zhang International Conference on Machine Learning, 13825-13856, 2022 | 1 | 2022 |
| Necessary and sufficient conditions for multiple objective optimal regression designs LL Gao, JJ Ye, S Zeng, J Zhou arXiv preprint arXiv:2303.04746, 2023 | | 2023 |
| Hierarchical Optimization-Derived Learning R Liu, X Liu, S Zeng, J Zhang, Y Zhang arXiv preprint arXiv:2302.05587, 2023 | | 2023 |
| A modularized algorithmic framework for interface related optimization problems using characteristic functions D Wang, S Zeng, J Zhang arXiv preprint arXiv:2206.01876, 2022 | | 2022 |
Jin ZhangSouthern University of Science and TechnologyVerified email at sustech.edu.cn
