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1 Ergebnisse
1
FedCSA: Boosting the Convergence Speed of Federated Unlearn..:
, 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)
,
Wang, Zhen
;
Alghazzawi, Daniyal M
;
Cheng, Li
... - p. 388-393 , 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>FedCSA: Boosting the Convergence Speed of Federated Unlearning under Data Heterogeneity</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10491845&Exemplar=1&LAN=DE A1 Wang, Zhen A1 Alghazzawi, Daniyal M A1 Cheng, Li A1 Liu, Gaoyang A1 Wang, Chen A1 Cheng, Zeng A1 Yang, Yang YR 2023 K1 Training K1 Data privacy K1 Privacy K1 Limiting K1 Scalability K1 Data models K1 Robustness K1 Federated Unlearning K1 Federated Learning SP 388 OP 393 LK http://dx.doi.org/https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00083 DO https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom59178.2023.00083 SF ELIB - SuUB Bremen
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