A parameterized proximal point algorithm for separable convex optimization

In this paper, we develop a parameterized proximal point algorithm (P-PPA) for solving a class of separable convex programming problems subject to linear and convex constraints. The proposed algorithm is provable to be globally convergent with a worst-case O(1/t) convergence rate, wheret denotes the...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Bai, Jianchao, Zhang, Hongchao, Li, Jicheng
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 10.12.2018
Subjects:	Algorithms Computational geometry Convergence Convexity Iterative methods Mathematical programming Optimization Parameterization State of the art
ISSN:	2331-8422
Online Access:	Get full text
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