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Article: Auto-weighted Robust Federated Learning with Corrupted Data Sources

TitleAuto-weighted Robust Federated Learning with Corrupted Data Sources
Authors
Li, SNgai, CHEYe, FVoigt, T
Issue Date2022
Citation
ACM Transactions on Intelligent Systems and Technology, 2022, v. 13, p. 1-20 How to Cite?
DOI: http://dx.doi.org/10.1145/3517821
Persistent Identifierhttp://hdl.handle.net/10722/321013
ISI Accession Number ID
WOS:000877952100005

 

DC FieldValueLanguage
dc.contributor.authorLi, S-
dc.contributor.authorNgai, CHE-
dc.contributor.authorYe, F-
dc.contributor.authorVoigt, T-
dc.date.accessioned2022-11-01T04:45:22Z-
dc.date.available2022-11-01T04:45:22Z-
dc.date.issued2022-
dc.identifier.citationACM Transactions on Intelligent Systems and Technology, 2022, v. 13, p. 1-20-
dc.identifier.urihttp://hdl.handle.net/10722/321013-
dc.languageeng-
dc.relation.ispartofACM Transactions on Intelligent Systems and Technology-
dc.titleAuto-weighted Robust Federated Learning with Corrupted Data Sources-
dc.typeArticle-
dc.identifier.emailNgai, CHE: chngai@eee.hku.hk-
dc.identifier.authorityNgai, CHE=rp02656-
dc.identifier.doi10.1145/3517821-
dc.identifier.hkuros340950-
dc.identifier.volume13-
dc.identifier.spage1-
dc.identifier.epage20-
dc.identifier.isiWOS:000877952100005-

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