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

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 defin...

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Veröffentlicht in:	Journal of scientific computing Jg. 76; H. 1; S. 364 - 389
Hauptverfasser:	Xiao, Xiantao, Li, Yongfeng, Wen, Zaiwen, Zhang, Liwei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2018 Springer Nature B.V
Schlagworte:	Algorithms Computational Mathematics and Numerical Analysis Convergence Convex analysis Hyperplanes Jacobi matrix method Jacobian matrix Machine learning Mapping Mathematical and Computational Engineering Mathematical and Computational Physics Mathematics Mathematics and Statistics Methods Newton methods Nonlinear equations Optimization Partial differential equations Regularization Splitting Theoretical Semi-smoothness Operator splitting methods 90C30 65K05 Proximal mapping Newton method Composite convex programs
ISSN:	0885-7474, 1573-7691
Online-Zugang:	Volltext
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