DC FieldValueLanguage
dc.contributor.authorPopović, Miroslaven_US
dc.contributor.authorPopović, Markoen_US
dc.contributor.authorKaštelan, Ivanen_US
dc.contributor.authorĐukić, Miodragen_US
dc.contributor.authorGhilezan, Silviaen_US
dc.date.accessioned2023-10-12T12:50:34Z-
dc.date.available2023-10-12T12:50:34Z-
dc.date.issued2023-
dc.identifier.isbn979-8-3503-4772-2-
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/5176-
dc.description.abstractNowadays 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.en_US
dc.publisherIEEEen_US
dc.subjectdecentralized intelligence | distributed systems | edge computing | federated learning | Pythonen_US
dc.titleA Simple Python Testbed for Federated Learning Algorithmsen_US
dc.typeConference Paperen_US
dc.relation.conference2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023, Novi Sad, Serbiaen_US
dc.identifier.doi10.1109/ZINC58345.2023.10173859-
dc.identifier.scopus2-s2.0-85166234697-
dc.contributor.affiliationMathematicsen_US
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Artsen_US
dc.relation.firstpage148-
dc.relation.lastpage153-
dc.description.rankM33-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference Paper-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.orcid0000-0003-2253-8285-
Show simple item record

SCOPUSTM   
Citations

3
checked on Nov 19, 2024

Page view(s)

18
checked on Nov 19, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.