{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T03:13:18Z","timestamp":1784949198299,"version":"3.55.0"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"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":["62002399"],"award-info":[{"award-number":["62002399"]}],"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":["U20A20159"],"award-info":[{"award-number":["U20A20159"]}],"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":["U1711265"],"award-info":[{"award-number":["U1711265"]}],"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":["61972432"],"award-info":[{"award-number":["61972432"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Program for Guangdong Introducing Innovative and Entrepreneurial Teams","award":["2017ZT07X355"],"award-info":[{"award-number":["2017ZT07X355"]}]},{"DOI":"10.13039\/100016691","name":"Guangdong Provincial Pearl River Talents Program","doi-asserted-by":"publisher","award":["2017GC010465"],"award-info":[{"award-number":["2017GC010465"]}],"id":[{"id":"10.13039\/100016691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2023,7,1]]},"DOI":"10.1109\/tmc.2022.3148263","type":"journal-article","created":{"date-parts":[[2022,2,4]],"date-time":"2022-02-04T20:36:39Z","timestamp":1644006999000},"page":"3910-3924","source":"Crossref","is-referenced-by-count":54,"title":["Enabling Long-Term Cooperation in Cross-Silo Federated Learning: A Repeated Game Perspective"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8088-0428","authenticated-orcid":false,"given":"Ning","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6398-4949","authenticated-orcid":false,"given":"Qian","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9943-6020","authenticated-orcid":false,"given":"Xu","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2018.1700202"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2967772"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16960"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1561\/9781680837896"},{"key":"ref5","article-title":"Swiss Re and Chinese firm WeBank partner to explore use of AI in reinsurance.","year":"2021"},{"key":"ref6","article-title":"Mammogram assessment with NVIDIA Clara federated learning.","year":"2021"},{"key":"ref7","article-title":"The MELLODDY project.","author":"Hale","year":"2021"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488705"},{"key":"ref9","first-page":"16","article-title":"Using monthly data to improve quarterly model forecasts","volume":"20","author":"Miller","year":"1996","journal-title":"Federal Reserve Bank Minneapolis Quart. Rev."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejso.2013.05.008"},{"key":"ref11","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. 20th Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488877"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488906"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.23919\/JCIN.2021.9475121"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488679"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.3036944"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3118354"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155268"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS47774.2020.00094"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488743"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2021.3063517"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-306-47828-4_214"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2006.872882"},{"key":"ref24","article-title":"Free-riders in federated learning: Attacks and defenses","author":"Lin","year":"2019"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPS-ISA50397.2020.00014"},{"key":"ref26","first-page":"1846","article-title":"Free-rider attacks on model aggregation in federated learning","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Fraboni"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_8"},{"key":"ref28","article-title":"Differentially private cross-silo federated learning","author":"Heikkil\u00e4","year":"2020"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.23919\/APNOMS50412.2020.9236971"},{"key":"ref30","first-page":"493","article-title":"BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Zhang"},{"key":"ref31","first-page":"1","article-title":"Incentive mechanism design for federated learning with multi-dimensional private information","volume-title":"Proc. 18th Int. Symp. Model. Optim. Mobile Ad Hoc Wireless Netw.","author":"Ding"},{"issue":"1","key":"ref32","first-page":"165","article-title":"Optimal distributed online prediction using mini-batches","volume":"13","author":"Dekel","year":"2012","journal-title":"J. Mach. Learn. Res."},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155414"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623612"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737464"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.2196\/20891"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/OJCOMS.2020.3024778"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2020.3027306"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2018.2829506"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2006.886393"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2021.3071506"},{"key":"ref42","first-page":"4615","article-title":"Agnostic federated learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Mohri"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.2307\/2296617"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1006\/game.1996.0018"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1093\/acprof:oso\/9780195300796.001.0001"},{"key":"ref46","first-page":"1","article-title":"On the convergence of FedAvg on Non-IID data","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li"},{"key":"ref47","article-title":"Towards causal federated learning for enhanced robustness and privacy","author":"Francis","year":"2021"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2022.3198176"},{"key":"ref49","article-title":"Amazon lambda pricing.","year":"2021"},{"key":"ref50","first-page":"1","article-title":"Deep autoencoding Gaussian mixture model for unsupervised anomaly detection","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zong"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7755\/10144458\/09705098.pdf?arnumber=9705098","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,17]],"date-time":"2024-01-17T23:56:11Z","timestamp":1705535771000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9705098\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,1]]},"references-count":50,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2022.3148263","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":[[2023,7,1]]}}}