{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T17:29:15Z","timestamp":1779211755981,"version":"3.51.4"},"reference-count":15,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Network"],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/mnet.001.2200223","type":"journal-article","created":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T22:38:00Z","timestamp":1669415880000},"page":"136-143","source":"Crossref","is-referenced-by-count":9,"title":["Asynchronous Semi-Supervised Federated Learning with Provable Convergence in Edge Computing"],"prefix":"10.1109","volume":"36","author":[{"given":"Nan","family":"Yang","sequence":"first","affiliation":[{"name":"The University of Sydney,Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Yuan","sequence":"additional","affiliation":[{"name":"The University of Sydney,Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuning","family":"Zhang","sequence":"additional","affiliation":[{"name":"The University of Sydney,Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongkun","family":"Deng","sequence":"additional","affiliation":[{"name":"The University of Sydney,Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Bao","sequence":"additional","affiliation":[{"name":"The University of Sydney,Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","first-page":"arxiv-2008","article-title":"Benchmarking Semi-Supervised Federated Learning","author":"zhang","year":"2020","journal-title":"ArXiv e-prints"},{"key":"ref11","first-page":"596","article-title":"Fixmatch: Simplifying Semi-Supervised Learning With Consistency and Confidence","volume":"33","author":"sohn","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref12","article-title":"Fair Resource Allocation in Federated Learning","author":"li","year":"0","journal-title":"Proc In t &#x2018;l Conf Learning Representations"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1090\/S0273-0979-1983-15145-5"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-92307-5_50"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000265"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.101.2100328"},{"key":"ref6","first-page":"1273","article-title":"Communication-Efficient Learning of Deep Networks From Decentralized Data","author":"mcmahan","year":"2017","journal-title":"Artificial Intelligence and Statistics"},{"key":"ref5","first-page":"429","article-title":"Federated Optimization in Heterogeneous Networks","volume":"2","author":"li","year":"0","journal-title":"Proc Machine Learning and Systems"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00991"},{"key":"ref7","article-title":"Federated Semi-Supervised Learning With Inter-Client Consistency & Disjoint Learning","author":"jeong","year":"0","journal-title":"Proc Int'l Conf Learning Representations (ICLR)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737464"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TSUSC.2019.2932045"},{"key":"ref9","first-page":"arxiv-2109","article-title":"Fedcon: A Contrastive Framework for Federated Semi-Supervised Learning","author":"long","year":"2021","journal-title":"ArXiv e-prints"}],"container-title":["IEEE Network"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/65\/9963993\/09964018.pdf?arnumber=9964018","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:12:15Z","timestamp":1670872335000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9964018\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":15,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/mnet.001.2200223","relation":{},"ISSN":["0890-8044","1558-156X"],"issn-type":[{"value":"0890-8044","type":"print"},{"value":"1558-156X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}