张立卫Liwei Zhang

(教授)

 博士生导师  硕士生导师
学位:博士
性别:男
毕业院校:大连理工大学
所在单位:数学科学学院
电子邮箱:lwzhang@dlut.edu.cn

论文成果

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A Regularized Semi-Smooth Newton Method with Projection Steps for Composite Convex Programs

发表时间:2019-03-12 点击次数:

论文名称:A Regularized Semi-Smooth Newton Method with Projection Steps for Composite Convex Programs
论文类型:期刊论文
第一作者:Xiao, Xiantao
通讯作者:Wen, ZW (reprint author), Peking Univ, Beijing Int Ctr Math Res, Beijing, Peoples R China.
合写作者:Li, Yongfeng,Wen, Zaiwen,Zhang, Liwei
发表刊物:JOURNAL OF SCIENTIFIC COMPUTING
收录刊物:SCIE
卷号:76
期号:1
页面范围:364-389
ISSN号:0885-7474
关键字:Composite convex programs; Operator splitting methods; Proximal mapping; Semi-smoothness; Newton method
摘要:The goal of this paper is to study approaches to bridge the gap between first-order and second-order type methods for composite convex programs. Our key observations are: (1) Many well-known operator splitting methods, such as forward-backward splitting and Douglas-Rachford splitting, actually define a fixed-point mapping; (2) The optimal solutions of the composite convex program and the solutions of a system of nonlinear equations derived from the fixed-point mapping are equivalent. Solving this kind of system of nonlinear equations enables us to develop second-order type methods. These nonlinear equations may be non-differentiable, but they are often semi-smooth and their generalized Jacobian matrix is positive semidefinite due to monotonicity. By combining with a regularization approach and a known hyperplane projection technique, we propose an adaptive semi-smooth Newton method and establish its convergence to global optimality. Preliminary numerical results on -minimization problems demonstrate that our second-order type algorithms are able to achieve superlinear or quadratic convergence.
发表时间:2018-07-01