{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T14:44:39Z","timestamp":1777128279169,"version":"3.51.4"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2021YFF0704102"],"award-info":[{"award-number":["2021YFF0704102"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62221005"],"award-info":[{"award-number":["62221005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072066"],"award-info":[{"award-number":["62072066"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Cooperation Project of Chongqing Municipal Education Commission","award":["HZ2021008"],"award-info":[{"award-number":["HZ2021008"]}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"publisher","award":["CSTC2021ycjh-bgzxm0013"],"award-info":[{"award-number":["CSTC2021ycjh-bgzxm0013"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"publisher","award":["CSTB2022NSCQ-MSX0329"],"award-info":[{"award-number":["CSTB2022NSCQ-MSX0329"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tmc.2024.3388731","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T17:31:23Z","timestamp":1713288683000},"page":"11014-11028","source":"Crossref","is-referenced-by-count":2,"title":["Cycle-Fed: A Double-Confidence Unlabeled Data Augmentation Method Based on Semisupervised Federated Learning"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2846-3571","authenticated-orcid":false,"given":"Yunpeng","family":"Xiao","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommnications, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2136-1465","authenticated-orcid":false,"given":"Qunqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommnications, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0048-9876","authenticated-orcid":false,"given":"Fei","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommnications, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7963-1766","authenticated-orcid":false,"given":"Rong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommnications, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3905-8173","authenticated-orcid":false,"given":"Qian","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommnications, Chongqing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8521-5232","authenticated-orcid":false,"given":"Guoyin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Chongqing University of Posts and Telecommnications, Chongqing, China"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2023.3265010"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3219485"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3096076"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482345"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/BigData52589.2021.9671693"},{"key":"ref8","first-page":"5049","article-title":"MixMatch: A holistic approach to semi-supervised learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Berthelot"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/jiot.2022.3151945"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01374"},{"key":"ref11","first-page":"12 846","article-title":"Asymmetric loss functions for learning with noisy labels","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","author":"Zhou"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00519"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2020.3009406"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00369"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref16","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Workshop Challenges Representation Learn.","author":"Lee"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3132056"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3129371"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2021.3070013"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3092015"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3519311"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2022.3151466"},{"key":"ref23","first-page":"954","article-title":"CMFL: Mitigating communication overhead for federated learning","volume-title":"Proc. IEEE 39th Int. Conf. Distrib. Comput. Syst.","author":"Luping"},{"key":"ref24","first-page":"5132","article-title":"SCAFFOLD: Stochastic controlled averaging for federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Karimireddy"},{"key":"ref25","article-title":"Federated learning based on dynamic regularization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Durmus"},{"key":"ref26","first-page":"2642","article-title":"Conditional image synthesis with auxiliary classifier GANs","volume-title":"Proc. 34th Int. Conf. Mach. Learn.","author":"Odena"},{"key":"ref27","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume-title":"Proc. Mach. Learn. Syst.","author":"Li"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00279"},{"key":"ref29","first-page":"13 344","article-title":"Federated learning with positive and unlabeled data","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Lin"},{"key":"ref30","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref31","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017"},{"key":"ref32","article-title":"Reading digits in natural images with unsupervised feature learning","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Netzer"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7755\/10746253\/10499842.pdf?arnumber=10499842","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:59Z","timestamp":1732665659000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10499842\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":32,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2024.3388731","relation":{},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"value":"1536-1233","type":"print"},{"value":"1558-0660","type":"electronic"},{"value":"2161-9875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}