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Efficiently Detecting Anomalies in IoT: A Novel Multi-Task ..:
, In:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Collaborative Computing: Networking, Applications and Worksharing
,
Hao, Junfeng
;
Chen, Juan
;
Chen, Peng
... - p. 100-117 , 2024
Link:
https://doi.org/10.1007/978-3-031-54531-3_6
RT T1 <cTitle>Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering; Collaborative Computing: Networking, Applications and Worksharing</cTitle>: T1 <Title>Efficiently Detecting Anomalies in IoT: A Novel Multi-Task Federated Learning Method</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_978-3-031-54531-3_6&Exemplar=1&LAN=DE A1 Hao, Junfeng A1 Chen, Juan A1 Chen, Peng A1 Wang, Yang A1 Niu, Xianhua A1 Xu, Lei A1 Xia, Yunni PB Springer Nature Switzerland YR 2024 SP 100 OP 117 LK http://dx.doi.org/https://doi.org/10.1007/978-3-031-54531-3_6 DO https://doi.org/10.1007/978-3-031-54531-3_6 SF ELIB - SuUB Bremen
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