{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T04:49:08Z","timestamp":1782362948789,"version":"3.54.5"},"reference-count":16,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T00:00:00Z","timestamp":1665273600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T00:00:00Z","timestamp":1665273600000},"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","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,9]]},"DOI":"10.1109\/smc53654.2022.9945192","type":"proceedings-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T20:49:04Z","timestamp":1668804544000},"page":"840-845","source":"Crossref","is-referenced-by-count":3,"title":["FedGosp: A Novel Framework of Gossip Federated Learning for Data Heterogeneity"],"prefix":"10.1109","author":[{"given":"Guanghao","family":"Li","sequence":"first","affiliation":[{"name":"National University of Defense Technology,College of Systems Engineering,Changsha,China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Hu","sequence":"additional","affiliation":[{"name":"National University of Defense Technology,College of Systems Engineering,Changsha,China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Zhang","sequence":"additional","affiliation":[{"name":"National University of Defense Technology,College of Systems Engineering,Changsha,China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[{"name":"University of Macau,IOTSC,Macau,China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Chang","sequence":"additional","affiliation":[{"name":"National University of Defense Technology,College of Computer,Changsha,China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quanjun","family":"Yin","sequence":"additional","affiliation":[{"name":"National University of Defense Technology,College of Systems Engineering,Changsha,China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","first-page":"5132","article-title":"Scaffold: Stochastic controlled averaging for federated learning","author":"karimireddy","year":"2020","journal-title":"International Conference on Machine Learning"},{"key":"ref11","author":"hanzely","year":"2020","journal-title":"Federated learning of a mixture of global and local models"},{"key":"ref12","first-page":"19","article-title":"Oort: Efficient federated learning via guided participant selection","author":"lai","year":"2021","journal-title":"15th USENIX Symposium on Operating Systems Design and Implementation ( OSDI 21)"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155494"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/BigData47090.2019.9006216"},{"key":"ref15","article-title":"Federated learning on non-iid data silos: An experimental study","author":"li","year":"2021","journal-title":"arXiv preprint arXiv 2102 09032"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.102.3.419"},{"key":"ref4","article-title":"Federated evaluation of on-device personalization","author":"wang","year":"2019","journal-title":"arXiv preprint arXiv 1910 10335"},{"key":"ref3","article-title":"Distilling the knowledge in a neural network","volume":"2","author":"hinton","year":"2015","journal-title":"arXiv preprint arXiv 1503 02531"},{"key":"ref6","article-title":"Salvaging federated learning by local adaptation","author":"yu","year":"2020","journal-title":"arXiv preprint arXiv 2002 01387"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.2858"},{"key":"ref8","first-page":"2089","article-title":"Exploiting shared representations for personalized federated learning","author":"collins","year":"2021","journal-title":"International Conference on Machine Learning"},{"key":"ref7","article-title":"Three approaches for personalization with applications to federated learning","author":"mansour","year":"2020","journal-title":"arXiv preprint arXiv 2002 10381"},{"key":"ref2","article-title":"Federated learning with non-iid data","author":"zhao","year":"2018","journal-title":"arXiv preprint arXiv 1806 00582"},{"key":"ref1","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":"ref9","first-page":"429","volume":"2","author":"li","year":"2020","journal-title":"Federated Optimization in Heterogeneous Networks"}],"event":{"name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","location":"Prague, Czech Republic","start":{"date-parts":[[2022,10,9]]},"end":{"date-parts":[[2022,10,12]]}},"container-title":["2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9945068\/9945069\/09945192.pdf?arnumber=9945192","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:53:52Z","timestamp":1670874832000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9945192\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,9]]},"references-count":16,"URL":"https:\/\/doi.org\/10.1109\/smc53654.2022.9945192","relation":{},"subject":[],"published":{"date-parts":[[2022,10,9]]}}}