{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T14:54:24Z","timestamp":1785336864420,"version":"3.55.0"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62071090"],"award-info":[{"award-number":["62071090"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100012542","name":"Sichuan Science and Technology Program","doi-asserted-by":"publisher","award":["2021YFH0014"],"award-info":[{"award-number":["2021YFH0014"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Wireless Commun."],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1109\/twc.2022.3221797","type":"journal-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T20:45:33Z","timestamp":1668804333000},"page":"3853-3868","source":"Crossref","is-referenced-by-count":38,"title":["Over-the-Air Federated Multi-Task Learning Over MIMO Multiple Access Channels"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2597-9206","authenticated-orcid":false,"given":"Chenxi","family":"Zhong","sequence":"first","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8400-146X","authenticated-orcid":false,"given":"Huiyuan","family":"Yang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0433-6535","authenticated-orcid":false,"given":"Xiaojun","family":"Yuan","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.2974748"},{"key":"ref35","author":"lecun","year":"1998","journal-title":"The MNIST Database of Handwritten Digits"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2007.904785"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOM.2018.8648097"},{"key":"ref37","article-title":"Deep learning for classical Japanese literature","author":"clanuwat","year":"2018","journal-title":"arXiv 1812 01718"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3039309"},{"key":"ref36","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"xiao","year":"2017","journal-title":"ArXiv 1708 07747"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3104834"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2014.2365813"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2021.3121067"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CDC.1995.478953"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2022.3153068"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1137\/110830629"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ISNCC55209.2022.9851727"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3086116"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511841224"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2946245"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2018.2812733"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2961673"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2021.3102601"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3118348"},{"key":"ref23","first-page":"13551","article-title":"ScaleCom: Scalable sparsified gradient compression for communication-efficient distributed training","volume":"33","author":"chen","year":"2020","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2022.3143217"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3043787"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ISIT45174.2021.9517780"},{"key":"ref22","first-page":"1","article-title":"Learning both weights and connections for efficient neural network","volume":"28","author":"han","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.23919\/JCC.2020.09.009"},{"key":"ref28","year":"2017","journal-title":"Lte Evolved Universal Terrestrial Radio Access (E-utra) Physical Layer Procedures"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2021.3090323"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/WCNC.2013.6555020"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3088910"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3037554"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2022.3150004"},{"key":"ref4","article-title":"Federated optimization: Distributed machine learning for on-device intelligence","author":"kone?n\u00fd","year":"2016","journal-title":"arXiv 1610 02527"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2018.2840738"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3183295"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2020.3002988"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2019.2936025"}],"container-title":["IEEE Transactions on Wireless Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7693\/10147751\/09955571.pdf?arnumber=9955571","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T18:55:44Z","timestamp":1687805744000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9955571\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6]]},"references-count":40,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/twc.2022.3221797","relation":{},"ISSN":["1536-1276","1558-2248"],"issn-type":[{"value":"1536-1276","type":"print"},{"value":"1558-2248","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6]]}}}