An efficient inexact symmetric Gauss–Seidel based majorized ADMM for high-dimensional convex composite conic programming

In this paper, we propose an inexact multi-block ADMM-type first-order method for solving a class of high-dimensional convex composite conic optimization problems to moderate accuracy. The design of this method combines an inexact 2-block majorized semi-proximal ADMM and the recent advances in the i...

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Bibliographic Details
Published in:	Mathematical programming Vol. 161; no. 1-2; pp. 237 - 270
Main Authors:	Chen, Liang, Sun, Defeng, Toh, Kim-Chuan
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2017 Springer Nature B.V
Subjects:	Accuracy Calculus of Variations and Optimal Control; Optimization Combinatorics Conics Convergence Convex analysis Cost engineering Criteria Full Length Paper Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematical programming Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Optimization Principal components analysis Quadratic programming Semidefinite programming Studies Symmetry Theoretical Convex quadratic semidefinite programming Alternating direction method of multipliers 65K05 90C25 90C22 Convex conic programming Majorization 90C06 Symmetric Gauss–Seidel
ISSN:	0025-5610, 1436-4646
Online Access:	Get full text
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