{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T17:52:06Z","timestamp":1775065926259,"version":"3.50.1"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"15","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"General Program of National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072049"],"award-info":[{"award-number":["62072049"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["4232029"],"award-info":[{"award-number":["4232029"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2023,8,1]]},"DOI":"10.1109\/jiot.2023.3262669","type":"journal-article","created":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T19:03:24Z","timestamp":1680030204000},"page":"13601-13611","source":"Crossref","is-referenced-by-count":9,"title":["FedUSC: Collaborative Unsupervised Representation Learning From Decentralized Data for Internet of Things"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8614-5080","authenticated-orcid":false,"given":"Chen","family":"Zhao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0563-6396","authenticated-orcid":false,"given":"Zhipeng","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7848-5421","authenticated-orcid":false,"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6513-1712","authenticated-orcid":false,"given":"Qian","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Beijing University of Technology, Beijing, China"}]},{"given":"Zijia","family":"Mo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"given":"Xinlei","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Federated learning with non-IID data","author":"zhao","year":"2018","journal-title":"arXiv 1806 00582"},{"key":"ref12","article-title":"Federated optimization in heterogeneous networks","author":"sahu","year":"2018","journal-title":"arXiv 1812 06127"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19821-2_29"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19214-2_15"},{"key":"ref10","article-title":"Federated semi-supervised learning with inter-client consistency & disjoint learning","author":"jeong","year":"2020","journal-title":"arXiv 2006 12097"},{"key":"ref17","article-title":"Orchestra: Unsupervised federated learning via globally consistent clustering","author":"lubana","year":"2022","journal-title":"arXiv 2205 11506"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.21437\/Interspeech.2022-10644"},{"key":"ref19","article-title":"Federated learning from only unlabeled data with class-conditional-sharing clients","author":"lu","year":"2022","journal-title":"arXiv 2204 03304"},{"key":"ref18","article-title":"Divergence-aware federated self-supervised learning","author":"zhuang","year":"2022","journal-title":"arXiv 2204 04385"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2021.3081748"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104319"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref48","first-page":"7611","article-title":"Tackling the objective inconsistency problem in heterogeneous federated optimization","volume":"33","author":"wang","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00077"},{"key":"ref42","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref41","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","author":"sohn","year":"2020","journal-title":"arXiv 2001 07685"},{"key":"ref44","first-page":"215","article-title":"An analysis of single-layer networks in unsupervised feature learning","author":"coates","year":"2011","journal-title":"Proc 14th Int Conf Artif Intell Stat"},{"key":"ref43","author":"netzer","year":"2011","journal-title":"Reading digits in natural images with unsupervised feature learning"},{"key":"ref49","article-title":"Unsupervised representation learning by predicting image rotations","author":"gidaris","year":"2018","journal-title":"arXiv 1803 07728"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3125989"},{"key":"ref7","article-title":"Federated unsupervised representation learning","author":"zhang","year":"2020","journal-title":"arXiv 2010 08982"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.08.009"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_16"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737464"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3143529"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3099368"},{"key":"ref40","article-title":"On mutual information maximization for representation learning","author":"tschannen","year":"2019","journal-title":"arXiv 1907 13625"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58607-2_16"},{"key":"ref34","article-title":"Big self-supervised models are strong semi-supervised learners","author":"chen","year":"2020","journal-title":"arXiv 2006 10029"},{"key":"ref37","article-title":"Unsupervised data augmentation","author":"xie","year":"2019","journal-title":"arXiv 1904 12848"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-24383-7_7"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475182"},{"key":"ref30","article-title":"Towards unsupervised domain adaptation for deep face recognition under privacy constraints via federated learning","author":"zhuang","year":"2021","journal-title":"arXiv 2105 07606"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944481"},{"key":"ref32","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"chen","year":"2020","journal-title":"Proc 7th Int Conf Machine Learning"},{"key":"ref2","article-title":"Federated learning for mobile keyboard prediction","author":"hard","year":"2018","journal-title":"arXiv 1811 03604"},{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume":"54","author":"mcmahan","year":"2017","journal-title":"Mach Learn Res"},{"key":"ref39","article-title":"Learning representations by maximizing mutual information across views","author":"bachman","year":"2019","journal-title":"arXiv 1906 00910"},{"key":"ref38","article-title":"RandAugment: Practical data augmentation with no separate search","author":"cubuk","year":"2019","journal-title":"arXiv 1909 13719"},{"key":"ref24","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"2014","journal-title":"Computer Vision"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS51616.2021.00010"},{"key":"ref26","article-title":"Distillation-based semi-supervised federated learning for communication-efficient collaborative training with non-iid private data","author":"itahara","year":"2020","journal-title":"arXiv 2008 06180"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9413428"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00487"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00099"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2953131"},{"key":"ref28","article-title":"Towards utilizing unlabeled data in federated learning: A survey and prospective","author":"jin","year":"2020","journal-title":"arXiv 2002 11545"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3092015"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3378679.3394530"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488907\/10194321\/10083198.pdf?arnumber=10083198","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T17:59:59Z","timestamp":1692035999000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10083198\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,1]]},"references-count":51,"journal-issue":{"issue":"15"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2023.3262669","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,1]]}}}