Liang Chen
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An efficient inexact symmetric Gauss–Seidel based majorized ADMM for high-dimensional convex composite conic programming
L Chen, D Sun, KC Toh
Mathematical Programming 161 (1-2), 237-270, 2017
912017
A note on the convergence of ADMM for linearly constrained convex optimization problems
L Chen, D Sun, KC Toh
Computational optimization and applications 66 (2), 327-343, 2017
332017
On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming
L Chen, X Li, D Sun, KC Toh
Mathematical Programming, 1-51, 2019
162019
A generalized alternating direction method of multipliers with semi-proximal terms for convex composite conic programming
Y Xiao, L Chen, D Li
Mathematical Programming Computation 10 (4), 533-555, 2018
82018
A three-operator splitting perspective of a three-block ADMM for convex quadratic semidefinite programming and extensions
X Chang, L Chen, S Liu
arXiv, 2018
8*2018
A Unified Algorithmic Framework of Symmetric Gauss-Seidel Decomposition based Proximal ADMMs for Convex Composite Programming
L Chen, D Sun, KC Toh, N Zhang
arXiv preprint arXiv:1812.06579, 2018
12018
On the Convergence Properties of a Second-Order Augmented Lagrangian Method for Nonlinear Programming Problems with Inequality Constraints
L Chen, A Liao
Journal of Optimization Theory and Applications, 1-18, 2015
12015
On the Linear and Asymptotically Superlinear Convergence Rates of the Augmented Lagrangian Method with a Practical Relative Error Criterion
XY Zhao, L Chen
arXiv preprint arXiv:1910.06937, 2019
2019
退化情形下高斯-赛德尔迭代法的几个问题
陈亮, 孙德锋, 卓金全
数值计算与计算机应用 40 (2), 98-110, 2018
2018
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Artiklar 1–9