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1 Ergebnisse
1
Disentangling Client Contributions: Improving Federated Lea..:
, 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)
,
Liu, Chunming
;
Alghazzawi, Daniyal M
;
Cheng, Li
... - p. 381-387 , 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>Disentangling Client Contributions: Improving Federated Learning Accuracy in the Presence of Heterogeneous Data</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10491709&Exemplar=1&LAN=DE A1 Liu, Chunming A1 Alghazzawi, Daniyal M A1 Cheng, Li A1 Liu, Gaoyang A1 Wang, Chen A1 Zeng, Cheng A1 Yang, Yang YR 2023 K1 Solid modeling K1 Data privacy K1 Costs K1 Codes K1 Federated learning K1 Soft sensors K1 Data models K1 Federated Learning K1 Statistical Heterogeneity K1 Aggregation Strategy SP 381 OP 387 LK http://dx.doi.org/https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00082 DO https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00082 SF ELIB - SuUB Bremen
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