The symmetric ADMM with indefinite proximal regularization and its application

The symmetric ADMM with indefinite proximal regularization and its application

Abstract Due to updating the Lagrangian multiplier twice at each iteration, the symmetric alternating direction method of multipliers (S-ADMM) often performs better than other ADMM-type methods. In practical applications, some proximal terms with positive definite proximal matrices are often added t...

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Bibliographic Details
Main Authors: Hongchun Sun, Maoying Tian, Min Sun
Format: Article
Language:English
Published: SpringerOpen 2017-07-01
Series:Journal of Inequalities and Applications
Subjects:
symmetric alternating direction method of multipliers
indefinite proximal regularization
global convergence
Online Access:http://link.springer.com/article/10.1186/s13660-017-1447-3

Internet

http://link.springer.com/article/10.1186/s13660-017-1447-3

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