{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T20:14:09Z","timestamp":1778530449231,"version":"3.51.4"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFE0208800"],"award-info":[{"award-number":["2023YFE0208800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation and Technology Commission of Hong Kong","award":["MHP\/072\/23"],"award-info":[{"award-number":["MHP\/072\/23"]}]},{"name":"Research Grants Council of Hong Kong Special Administrative Region, China","award":["CityU 11202925"],"award-info":[{"award-number":["CityU 11202925"]}]},{"name":"Research Grants Council of Hong Kong Special Administrative Region, China","award":["CityU 11202124"],"award-info":[{"award-number":["CityU 11202124"]}]},{"name":"Research Grants Council of Hong Kong Special Administrative Region, China","award":["CityU 11217823"],"award-info":[{"award-number":["CityU 11217823"]}]},{"name":"Research Grants Council of Hong Kong Special Administrative Region, China","award":["CityU 11216225"],"award-info":[{"award-number":["CityU 11216225"]}]},{"name":"Collaborative Research Fund","award":["C1042-23GF"],"award-info":[{"award-number":["C1042-23GF"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62371411"],"award-info":[{"award-number":["62371411"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"InnoHK initiative","award":["MHP\/072\/23"],"award-info":[{"award-number":["MHP\/072\/23"]}]},{"name":"InnoHK initiative","award":["11202925"],"award-info":[{"award-number":["11202925"]}]},{"name":"InnoHK initiative","award":["11202124"],"award-info":[{"award-number":["11202124"]}]},{"name":"InnoHK initiative","award":["11217823"],"award-info":[{"award-number":["11217823"]}]},{"name":"InnoHK initiative","award":["11216225"],"award-info":[{"award-number":["11216225"]}]},{"name":"InnoHK initiative","award":["C1042-23GF"],"award-info":[{"award-number":["C1042-23GF"]}]},{"name":"InnoHK initiative","award":["62371411"],"award-info":[{"award-number":["62371411"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1109\/tcsvt.2025.3645323","type":"journal-article","created":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T18:49:09Z","timestamp":1765997349000},"page":"7307-7321","source":"Crossref","is-referenced-by-count":0,"title":["Robust Federated Learning Under Heterogeneity via Rank-One and Column-Sparsity Model"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4693-9430","authenticated-orcid":false,"given":"Zhi-Yong","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3557-5424","authenticated-orcid":false,"given":"Hao","family":"Nan Sheng","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8396-7898","authenticated-orcid":false,"given":"Hing","family":"Cheung So","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6157-2051","authenticated-orcid":false,"given":"Jiande","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shandong Normal University, Jinan, Shandong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2756-4984","authenticated-orcid":false,"given":"Linqi","family":"Song","sequence":"additional","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9741-5912","authenticated-orcid":false,"given":"Weitao","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. AISTATS","author":"McMahan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1561\/2200000083"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-96896-0"},{"key":"ref4","volume-title":"Federated Learning: Theory and Practice","author":"Nguyen","year":"2024"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3310400"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tcsvt.2024.3519790"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3325822"},{"issue":"3","key":"ref8","first-page":"157","article-title":"AI and machine learning in banking: A systematic literature review","volume":"6","author":"Donepudi","year":"2017","journal-title":"Asian J. Appl. Sci. Eng."},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3016035"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3407131"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2021.3077893"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IOTM.001.2100192"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3266347"},{"key":"ref14","first-page":"1","article-title":"Certifiably Byzantine-robust federated conformal prediction","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Kang"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3128164"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/357172.357176"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3362147"},{"key":"ref18","first-page":"118","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. NIPS","author":"Blanchard"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011544"},{"key":"ref20","first-page":"5311","article-title":"Learning from history for Byzantine robust optimization","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"139","author":"Karimireddy"},{"key":"ref21","first-page":"83","article-title":"Fall of empires: Breaking Byzantine-tolerant SGD by inner product manipulation","volume-title":"Proc. UAI","author":"Xie"},{"key":"ref22","first-page":"1","article-title":"Byzantine-resilient non-convex stochastic gradient descent","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Allen-Zhu"},{"key":"ref23","first-page":"8632","article-title":"A little is enough: Circumventing defenses for distributed learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Baruch"},{"key":"ref24","first-page":"5636","article-title":"Byzantine-robust distributed learning: Towards optimal statistical rates","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yin"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3153135"},{"key":"ref26","first-page":"1","article-title":"Byzantine-robust learning on heterogeneous datasets via bucketing","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Karimireddy"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1017\/9781139084291"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3616537"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3465084.3467902"},{"key":"ref30","first-page":"1232","article-title":"Fixing by mixing: A recipe for optimal Byzantine ML under heterogeneity","volume-title":"Proc. AISTATS","author":"Allouah"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-0688-4"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2025.3628486"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i19.30181"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2023.3290353"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2908833"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2024.3424272"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3114208"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2024.109666"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3214583"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2019.2923816"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382273"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2022.3206881"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i15.29584"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/670"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2024.3383294"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.101016\/j.cosrev.2016.11.001"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3224070"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1982"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2020.3012952"},{"key":"ref50","first-page":"1","article-title":"Variance reduction is an antidote to Byzantines: Better rates, weaker assumptions and communication compression as a cherry on the top","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Gorbunov"},{"key":"ref51","first-page":"6246","article-title":"Byzantine machine learning made easy by resilient averaging of momentums","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Farhadkhani"},{"key":"ref52","first-page":"1","article-title":"Distributed momentum for Byzantine-resilient stochastic gradient descent","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Mhamdi"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"ref54","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017","journal-title":"arXiv:1708.07747"},{"key":"ref55","volume-title":"CIFAR-10 (Canadian Institute for Advanced Research)","author":"Krizhevsky","year":"2010"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref57","article-title":"Measuring the effects of non-identical data distribution for federated visual classification","author":"Harry Hsu","year":"2019","journal-title":"arXiv:1909.06335"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/76\/11511351\/11303260.pdf?arnumber=11303260","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T19:48:46Z","timestamp":1778528926000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11303260\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":57,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2025.3645323","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"value":"1051-8215","type":"print"},{"value":"1558-2205","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5]]}}}