A Proximal Alternating Direction Method of Multipliers for DC Programming with Structured Constraints

In this paper, we consider a class of structured DC programming, where the objective function is the difference of two (possibly nonsmooth) convex functions, and the constraint is a linear function belonging to a nonempty closed convex set. To fully exploit the favorable structure of the problem und...

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Veröffentlicht in:	Journal of scientific computing Jg. 99; H. 3; S. 89
Hauptverfasser:	Zhou, Yingxin, He, Hongjin, Zhang, Linan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.06.2024 Springer Nature B.V
Schlagworte:	Algorithms Computational Mathematics and Numerical Analysis Convexity Critical point Linear functions Mathematical and Computational Engineering Mathematical and Computational Physics Mathematical functions Mathematics Mathematics and Statistics Multipliers Operators (mathematics) Optimization Theoretical Variables Alternating direction method of multipliers Nonconvex optimization DC programming 90C90 90C26 Dantzig selector Kurdyka–Łojasiewicz inequality
ISSN:	0885-7474, 1573-7691
Online-Zugang:	Volltext
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