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Yuan Shen
Yuan Shen
Doctor of Mathematics, Nanjing University of Finance & Economics
Verified email at njue.edu.cn
Title
Cited by
Cited by
Year
Augmented Lagrangian alternating direction method for matrix separation based on low-rank factorization
Y Shen, Z Wen, Y Zhang
Taylor & Francis, 2012
3162012
On the convergence analysis of the alternating direction method of multipliers with three blocks
C Chen, Y Shen, Y You
Abstract and Applied Analysis 2013, 2013
672013
On the convergence rate of customized proximal point algorithm for convex optimization and saddle-point problem (in Chinese)
B He, Y Shen
Sci Sin Math 42 (5), 515--525, 2012
152012
A partially proximal S-ADMM for separable convex optimization with linear constraints
Y Shen, Y Zuo, A Yu
Applied Numerical Mathematics 160, 65-83, 2021
82021
On the O (1/t) convergence rate of Ye–Yuan’s modified alternating direction method of multipliers
Y Shen, M Xu
Applied Mathematics and Computation 226, 367-373, 2014
82014
A partial PPA block-wise ADMM for multi-block linearly constrained separable convex optimization
Y Shen, X Zhang, X Zhang
Optimization 70 (3), 631-657, 2021
72021
An alternating minimization method for robust principal component analysis
Y Shen, H Xu, X Liu
Optimization Methods and Software 34 (6), 1251-1276, 2019
62019
A multi-parameter parallel ADMM for multi-block linearly constrained separable convex optimization
Y Shen, Q Gao, X Yin
Applied Numerical Mathematics 171, 369-388, 2022
52022
Relaxed augmented Lagrangian-based proximal point algorithms for convex optimization with linear constraints
Y Shen, W Zhang, B He
J. Ind. Manag. Optim 10, 743-759, 2014
52014
Convergence study on strictly contractive Peaceman–Rachford splitting method for nonseparable convex minimization models with quadratic coupling terms
P Li, Y Shen, S Jiang, Z Liu, C Chen
Computational Optimization and Applications 78, 87-124, 2021
22021
New augmented Lagrangian-based proximal point algorithm for convex optimization with equality constraints
Y Shen, H Wang
Journal of Optimization Theory and Applications 171, 251-261, 2016
22016
A relaxed parameter condition for the primal-dual hybrid gradient method for saddle-point problem
X Zhang, Y Kong, S Liu, Y Shen
Journal of Industrial and Management Optimization 19 (3), 1595-1610, 2023
12023
A faster generalized ADMM-based algorithm using a sequential updating scheme with relaxed step sizes for multiple-block linearly constrained separable convex programming
Y Shen, Y Zuo, X Zhang
Journal of Computational and Applied Mathematics 393, 113503, 2021
12021
An alternating minimization method for matrix completion problems
Y Shen, X Liu
Discrete and Continuous Dynamical Systems-S 13 (6), 1757-1772, 2020
12020
A partial PPa S-ADMM for multi-block for separable convex optimization with linear constraints
Y Shen, Y Zuo, A Yu
Optimization online, 2020
12020
Partial convolution for total variation deblurring and denoising by new linearized alternating direction method of multipliers with extension step
Y Shen, L Ji
Journal of Industrial & Management Optimization 15 (1), 159, 2019
12019
A modified self-adaptive dual ascent method with relaxed stepsize condition for linearly constrained quadratic convex optimization
Y Shen, C Liu, Y Zuo, X Zhang
Journal of Industrial and Management Optimization 19 (5), 3637-3649, 2023
2023
Trace minimization method via penalty for linear response eigenvalue problems
Y Chen, Y Shen, S Liu
Journal of Industrial and Management Optimization 19 (1), 773-791, 2022
2022
Modified proximal symmetric ADMMs for multi-block separable convex optimization with linear constraints
Y Shen, Y Zuo, L Sun, X Zhang
Analysis and Applications 20 (03), 401-428, 2022
2022
A Self-Adaptive Projection and Contraction Method for Optimizing the Sum of a Convex and a Quadratic Function
Y Shen, C Wang
Pacific Journal of Optimization 9 (1), 137-154, 2013
2013
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