Distributed stochastic mirror descent algorithm for resource allocation problem

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	Distributed stochastic mirror descent algorithm for resource allocation problem
	Wang Yinghui; Tu Zhipeng; Qin Huashu
	2020
发表期刊	Control Theory and Technology
ISSN	2095-6983
卷号	18 期号:4 页码:339-347
摘要	In this paper, we consider a distributed resource allocation problem of minimizing a global convex function formed by a sum of local convex functions with coupling constraints. Based on neighbor communication and stochastic gradient, a distributed stochastic mirror descent algorithm is designed for the distributed resource allocation problem. Sublinear convergence to an optimal solution of the proposed algorithm is given when the second moments of the gradient noises are summable. A numerical example is also given to illustrate the effectiveness of the proposed algorithm.
关键词	Distributed Resource allocation problem Stochastic gradient Mirror descent
收录类别	CSCD
语种	英语
CSCD记录号	CSCD:6870881
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/58370
专题	中国科学院数学与系统科学研究院
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Wang Yinghui,Tu Zhipeng,Qin Huashu. Distributed stochastic mirror descent algorithm for resource allocation problem[J]. Control Theory and Technology,2020,18(4):339-347.
APA	Wang Yinghui,Tu Zhipeng,&Qin Huashu.(2020).Distributed stochastic mirror descent algorithm for resource allocation problem.Control Theory and Technology,18(4),339-347.
MLA	Wang Yinghui,et al."Distributed stochastic mirror descent algorithm for resource allocation problem".Control Theory and Technology 18.4(2020):339-347.