Liang Chen
chl@hnu.edu.cn
Chinese, English
Hunan
Hunan University
Mathematical Sciences
  • 2005-09-01—2009-06-18, Bachelor of Science: Hunan University, School of Mathematics and Econometrics
  • 2009-09-01—2016-12-27, Doctor of Science: Hunan University, School of Mathematics and Econometrics
  • 2013-08-01—2015-07-31, Joint PhD Student: National University of Singapore, Department of Mathematics
  • 2017-02-01—2017-08-31, National University of Singapore, Research Fellow
  • 2017-09-01—2019-08-31, Hong Kong Polytechnic University, Postdoctoral Fellow
  • 2023-02-01—2023-08-31, Hong Kong Polytechnic University, Research Fellow
  • 2015.12, Second Prize: Hunan Province Computational Mathematics and Application Software Society Young Outstanding Paper
  • 2020.12, First Prize: Hunan Province Computational Mathematics and Application Software Society Young Outstanding Paper
  • 2021.6, Outstanding Undergraduate Thesis Advisor: Hunan University
  • 2023.4, First Prize: Hunan Province Computational Mathematics and Application Software Society Young Outstanding Paper
Mathematical/Computational Optimization
Linear and Nonlinear Programming
Convex Programming
Matrix Optimization
Statistical Optimization
Operations Research
  • An efficient inexact symmetric Gauss-Seidel based majorized ADMM for high-dimensional convex composite conic programming, Liang Chen, Defeng Sun, and Kim-Chuan Toh, 2017
  • A note on the convergence of ADMM for linearly constrained convex optimization problems, Liang Chen, Defeng Sun, and Kim-Chuan Toh, 2017
  • A generalized alternating direction method of multipliers with semi-proximal terms for convex composite conic programming, Yunhai Xiao, Liang Chen, and Donghui Li, 2018
  • Some problems on the Gauss-Seidel iteration method in degenerate cases, Liang Chen, Defeng Sun, and Kim-Chuan Toh, 2019
  • A unified algorithmic framework of symmetric Gauss-Seidel decomposition based proximal ADMMs for convex composite programming, Liang Chen, Defeng Sun, Kim-Chuan Toh, and Ning Zhang, 2019
  • The linear and asymptotically superlinear convergence rates of the augmented Lagrangian method with a practical relative error criterion, Xin-Yuan Zhao, Liang Chen, 2020
  • A three-operator splitting perspective of a three-block ADMM for convex quadratic semidefinite programming and beyond, Liang Chen, Xiaokai Chang, and Sanyang Liu, 2020
  • On the convergence properties of a second-order augmented Lagrangian method for nonlinear programming problems with inequality constraints, Liang Chen, Anping Liao, 2020
  • On the equivalence of inexact proximal ALM and ADMM for a class of convex composite programming, Liang Chen, Xudong Li, Defeng Sun, and Kim-Chuan Toh, 2021
  • A modified exchange algorithm for distributional robust optimization and applications in risk management, Hailin Sun, Dali Zhang, Soon-Yi Wu, and Liang Chen, 2022
  • Unified convergence analysis of a second-order method of multipliers for nonlinear conic programming, Liang Chen, Junyuan Zhu, and Xinyuan Zhao, 2022
  • High-resolution short angle weight algorithm in sonar systems, Haoran Ji, Lei Wang, Cong Peng, Liang Chen, Shuhao Zhang, and Qian Zhou, 2023
  • Stochastic domain decomposition based on variable-separation method, Liang Chen, Yaru Chen, Qiuqi Li, and Zhiwen Zhang, 2024
Optimization Computational Linear Nonlinear Convex Matrix Statistical Operations Research Programming

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