{"title":"时变图的分散条件梯度方法","authors":"R. A. Vedernikov, A. V. Rogozin, A. V. Gasnikov","doi":"10.1134/s0361768823060075","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>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.</p>","PeriodicalId":54555,"journal":{"name":"Programming and Computer Software","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Decentralized Conditional Gradient Method on Time-Varying Graphs\",\"authors\":\"R. A. Vedernikov, A. V. Rogozin, A. V. Gasnikov\",\"doi\":\"10.1134/s0361768823060075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Abstract</h3><p>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.</p>\",\"PeriodicalId\":54555,\"journal\":{\"name\":\"Programming and Computer Software\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Programming and Computer Software\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1134/s0361768823060075\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Programming and Computer Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1134/s0361768823060075","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Decentralized Conditional Gradient Method on Time-Varying Graphs
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.
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.