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Shangzhi ZENG
Shangzhi ZENG
Department of Mathematics and Statistics, University of Victoria
Verified email at uvic.ca
Title
Cited by
Cited by
Year
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
1102020
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
542021
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
522021
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
382022
Averaged method of multipliers for bi-level optimization without lower-level strong convexity
R Liu, Y Liu, W Yao, S Zeng, J Zhang
International Conference on Machine Learning, 21839-21866, 2023
332023
Discerning the linear convergence of ADMM for structured convex optimization through the lens of variational analysis
X Yuan, S Zeng, J Zhang
Journal of Machine Learning Research 21 (83), 1-75, 2020
332020
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
302021
Difference of convex algorithms for bilevel programs with applications in hyperparameter selection
JJ Ye, X Yuan, S Zeng, J Zhang
Mathematical Programming 198 (2), 1583-1616, 2023
242023
A globally convergent proximal Newton-type method in nonsmooth convex optimization
BS Mordukhovich, X Yuan, S Zeng, J Zhang
Mathematical Programming 198 (1), 899-936, 2023
242023
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
232021
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
232018
Value-function-based sequential minimization for bi-level optimization
R Liu, X Liu, S Zeng, J Zhang, Y Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
182023
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
162022
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
16*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
112017
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
52022
Hierarchical optimization-derived learning
R Liu, X Liu, S Zeng, J Zhang, Y Zhang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
22023
Moreau envelope based difference-of-weakly-convex reformulation and algorithm for bilevel programs
LL Gao, JJ Ye, H Yin, S Zeng, J Zhang
arXiv preprint arXiv:2306.16761, 2023
22023
Augmenting iterative trajectory for bilevel optimization: Methodology, analysis and extensions
R Liu, Y Liu, S Zeng, J Zhang
arXiv preprint arXiv:2303.16397, 2023
12023
A modularized algorithmic framework for interface related optimization problems using characteristic functions
D Wang, S Zeng, J Zhang
arXiv preprint arXiv:2206.01876, 2022
12022
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