Adaptive Federated Learning in Resource Constrained Edge Computing Systems
IEEE Journal on Selected Areas in Communications(2019)
摘要
Emerging technologies and applications including Internet of Things, social networking, and crowd-sourcing generate large amounts of data at the network edge. Machine learning models are often built from the collected data, to enable the detection, classification, and prediction of future events. Due to bandwidth, storage, and privacy concerns, it is often impractical to send all the data to a cen...
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关键词
Machine learning,Data models,Convergence,Distributed databases,Machine learning algorithms,Training,Peer-to-peer computing
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