Decentralized Conditional Gradient Method on Time-Varying Graphs

IF 0.7 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Programming and Computer Software Pub Date : 2023-12-01 DOI:10.1134/s0361768823060075

R. A. Vedernikov, A. V. Rogozin, A. V. Gasnikov

引用次数: 0

Abstract

In this paper, we consider a generalization of the decentralized Frank–Wolfe algorithm to time-varying networks, investigate the convergence properties of the algorithm, and carry out the corresponding numerical experiments. The time-varying network is modeled as a deterministic or stochastic sequence of graphs.

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时变图的分散条件梯度方法

摘要本文将分散的Frank-Wolfe算法推广到时变网络，研究了该算法的收敛性，并进行了相应的数值实验。时变网络被建模为一个确定的或随机的图序列。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Programming and Computer Software 工程技术-计算机：软件工程

CiteScore

1.60

自引率

28.60%

发文量

审稿时长

>12 weeks

期刊介绍： Programming and Computer Software is a peer reviewed journal devoted to problems in all areas of computer science: operating systems, compiler technology, software engineering, artificial intelligence, etc.