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1 Ergebnisse
1
FedEntropy: Efficient Federated Learning for Non-IID Scenar..:
, In:
2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)
,
Ling, Zhiwei
;
Yue, Zhihao
;
Xia, Jun
... - p. 56-63 , 2023
Link:
https://doi.org/10.1109/ISPA-BDCloud-SocialCom-Sustain..
RT T1 <cTitle>2023 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)</cTitle>: T1 <Title>FedEntropy: Efficient Federated Learning for Non-IID Scenarios Using Maximum Entropy Judgment-based Client Selection</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10491750&Exemplar=1&LAN=DE A1 Ling, Zhiwei A1 Yue, Zhihao A1 Xia, Jun A1 Wang, Ting A1 Chen, Mingsong A1 Lian, Xiang YR 2023 K1 Training K1 Filters K1 Federated learning K1 Distributed databases K1 Benchmark testing K1 Entropy K1 Data models K1 Federated Learning K1 maximum entropy judgment K1 client selection K1 non-IID data distribution SP 56 OP 63 LK http://dx.doi.org/https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00040 DO https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00040 SF ELIB - SuUB Bremen
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