A primal-dual algorithm framework for convex saddle-point optimization

A primal-dual algorithm framework for convex saddle-point optimization

Abstract In this study, we introduce a primal-dual prediction-correction algorithm framework for convex optimization problems with known saddle-point structure. Our unified frame adds the proximal term with a positive definite weighting matrix. Moreover, different proximal parameters in the frame ca...

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Bibliographic Details
Main Authors: Benxin Zhang, Zhibin Zhu
Format: Article
Language:English
Published: SpringerOpen 2017-10-01
Series:Journal of Inequalities and Applications
Subjects:
primal-dual method
proximal point algorithm
convex optimization
variational inequalities
Online Access:http://link.springer.com/article/10.1186/s13660-017-1548-z

Internet

http://link.springer.com/article/10.1186/s13660-017-1548-z

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