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Federated learning with non-iid data. <u>arXiv preprint arXiv:1806.00582<\/u> (2018)."}],"event":{"name":"MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services","location":"Portland Oregon","acronym":"MobiSys '22","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3498361.3538917","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3498361.3538917","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:10:04Z","timestamp":1750183804000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3498361.3538917"}},"subtitle":["data and pace control for efficient federated learning on heterogeneous clients"],"short-title":[],"issued":{"date-parts":[[2022,6,27]]},"references-count":81,"alternative-id":["10.1145\/3498361.3538917","10.1145\/3498361"],"URL":"https:\/\/doi.org\/10.1145\/3498361.3538917","relation":{},"subject":[],"published":{"date-parts":[[2022,6,27]]},"assertion":[{"value":"2022-06-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}