Newton-Type Alternating Minimization Algorithm for Convex Optimization

We propose a Newton-type alternating minimization algorithm (NAMA) for solving structured nonsmooth convex optimization problems where the sum of two functions is to be minimized, one being strongly convex and the other composed with a linear mapping. The proposed algorithm is a line-search method o...

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Bibliographic Details
Published in:	IEEE transactions on automatic control Vol. 64; no. 2; pp. 697 - 711
Main Authors:	Stella, Lorenzo, Themelis, Andreas, Patrinos, Panagiotis
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.02.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Acceleration Algorithms Computational geometry Continuity (mathematics) Convergence Convergence of numerical methods Convex analysis Convex functions Convexity Gradient methods iterative methods Mapping Minimization optimal control Optimization Penalty function
ISSN:	0018-9286, 1558-2523
Online Access:	Get full text
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