A Simple Python Testbed for Federated Learning Algorithms

M. Popovic, M. Popovic, I. Kastelan, Miodrag Djukic, S. Ghilezan
{"title":"A Simple Python Testbed for Federated Learning Algorithms","authors":"M. Popovic, M. Popovic, I. Kastelan, Miodrag Djukic, S. Ghilezan","doi":"10.1109/ZINC58345.2023.10173859","DOIUrl":null,"url":null,"abstract":"Nowadays many researchers are developing various distributed and decentralized frameworks for federated learning algorithms. However, development of such a framework targeting smart Internet of Things in edge systems is still an open challenge. In this paper, we present our solution to that challenge called Python Testbed for Federated Learning Algorithms. The solution is written in pure Python, and it supports both centralized and decentralized algorithms. The usage of the presented solution is both validated and illustrated by three simple algorithm examples.","PeriodicalId":383771,"journal":{"name":"2023 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Zooming Innovation in Consumer Technologies Conference (ZINC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ZINC58345.2023.10173859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Nowadays many researchers are developing various distributed and decentralized frameworks for federated learning algorithms. However, development of such a framework targeting smart Internet of Things in edge systems is still an open challenge. In this paper, we present our solution to that challenge called Python Testbed for Federated Learning Algorithms. The solution is written in pure Python, and it supports both centralized and decentralized algorithms. The usage of the presented solution is both validated and illustrated by three simple algorithm examples.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
联邦学习算法的简单Python测试平台
目前,许多研究人员正在开发各种分布式和去中心化的联邦学习算法框架。然而,开发这样一个针对边缘系统中的智能物联网的框架仍然是一个开放的挑战。在本文中,我们提出了针对该挑战的解决方案,称为Python Testbed for Federated Learning Algorithms。该解决方案是用纯Python编写的,它支持集中式和分散式算法。通过三个简单的算法实例验证了该方法的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Representing Multifunctional Devices in Voice-Controlled Systems Improving Lane Annotation in Autonomous Driving Data Sets with Classical Computer Vision Techniques Security enhancement of LSB-based audio steganography method ZINC 2023 Organizing Team Travel Route Planning in Smart Cities
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1