Two new customized proximal point algorithms without relaxation for linearly constrained convex optimization
type: Item
instance of: scholarly article
title: Two new customized proximal point algorithms without relaxation for linearly constrained convex optimization
zbMATH Open document ID: 1447.90029
author: Zheng Peng
author: Kangkang Deng
author: Bin-Qian Jiang
published in: Bulletin of the Iranian Mathematical Society
publication date: 2020-07-14T00:00:00Z
Mathematics Subject Classification ID: 90C25
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 65K10
zbMATH DE Number: 7220177
zbMATH Keywords: convex optimization
zbMATH Keywords: separable convex optimization
zbMATH Keywords: customized proximal point algorithm
zbMATH Keywords: global convergence
zbMATH Keywords: \(\mathcal{O}(1/k)\)-convergence rate
MaRDI profile type: Publication
full work available at URL: s41980-019-00298-0
OpenAlex ID: W2982154129
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Wikidata QID: Q127025855
DOI: 10.1007/S41980-019-00298-0
description: scientific article; zbMATH DE number 7220177