Convergence Time Optimization for Federated Learning over Wireless Networks

IEEE Transactions on Wireless Communications(2021)

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摘要
In this paper, the convergence time of federated learning (FL), when deployed over a realistic wireless network, is studied. In particular, a wireless network is considered in which wireless users transmit their local FL models (trained using their locally collected data) to a base station (BS). The BS, acting as a central controller, generates a global FL model using the received local FL models ...
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关键词
Federated learning, wireless resource allocation,probabilistic user selection,artificial neural networks
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