Abstract: In the edge computing system, split learning (SL) is an emerging distributed learning approach that allows mobile users (MUs) and edge nodes (ENs) to train the model together without sharing ...
Abstract: Clients in federated learning (FL) may exhibit varying computing capabilities, leading to prolonged training latency when deploying complex deep neural networks. To address this challenge, ...
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