{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T21:36:06Z","timestamp":1771536966553,"version":"3.50.1"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2026.3662085","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T20:51:07Z","timestamp":1770411067000},"page":"24018-24029","source":"Crossref","is-referenced-by-count":0,"title":["Split Averaging: Bridging the Heterogeneity Gap in Clients Data for Federated Learning"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6608-5065","authenticated-orcid":false,"given":"Sajjad","family":"Khan","sequence":"first","affiliation":[{"name":"Department of Information Systems and Operations Management, Research Group for Information Systems and Applied AI, Vienna University of Economics and Business, Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8932-4164","authenticated-orcid":false,"given":"Nikita","family":"Karetnikov","sequence":"additional","affiliation":[{"name":"Department of Information Systems and Operations Management, Research Group for Information Systems and Applied AI, Vienna University of Economics and Business, Vienna, Austria"}]},{"given":"Muhammad Habib Ur","family":"Rehman","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, University of Bedfordshire, Luton, U.K."}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3020-9556","authenticated-orcid":false,"given":"Davor","family":"Svetinovic","sequence":"additional","affiliation":[{"name":"Center for Secure Cyber-Physical Systems, Computer Science, Khalifa University, Abu Dhabi, United Arab Emirates"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3541213"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3528373"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3543577"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3539336"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2023.100956"},{"key":"ref6","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist.","volume":"54","author":"McMahan"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3525806"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3529894"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.iot.2024.101174"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3075706"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2023.103714"},{"key":"ref12","first-page":"5834","article-title":"Federated learning under distributed concept drift","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Jothimurugesan"},{"key":"ref13","first-page":"2611","article-title":"Heterogeneity for the win: One-shot federated clustering","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Dennis"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3115952"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3160699"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3474056"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102344"},{"key":"ref18","article-title":"Federated learning with non-IID data","author":"Zhao","year":"2018","journal-title":"arXiv:1806.00582"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2021.3070013"},{"key":"ref20","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume":"2","author":"Tian","year":"2018","journal-title":"Proc. Mach. Learn. Syst."},{"key":"ref21","article-title":"Federated learning based on dynamic regularization","author":"Alp Emre Acar","year":"2021","journal-title":"arXiv:2111.04263"},{"key":"ref22","first-page":"5132","article-title":"SCAFFOLD: Stochastic controlled averaging for federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Karimireddy"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2023.01.019"},{"key":"ref25","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"Harry Hsu","year":"2019","journal-title":"arXiv:1909.06335"},{"key":"ref26","article-title":"FedCM: Federated learning with client-level momentum","author":"Xu","year":"2021","journal-title":"arXiv:2106.10874"},{"key":"ref27","first-page":"7611","article-title":"Tackling the objective inconsistency problem in heterogeneous federated optimization","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wang"},{"key":"ref28","article-title":"FedBN: Federated learning on non-IID features via local batch normalization","author":"Li","year":"2021","journal-title":"arXiv:2102.07623"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3323302"},{"key":"ref30","article-title":"Adaptive federated optimization","author":"Reddi","year":"2020","journal-title":"arXiv:2003.00295"},{"key":"ref31","article-title":"Learning from drift: Federated learning on non-IID data via drift regularization","author":"Kim","year":"2023","journal-title":"arXiv:2309.07189"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3271517"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3302410"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11373536.pdf?arnumber=11373536","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T20:59:30Z","timestamp":1771534770000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11373536\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3662085","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}