Abstract: Federated Learning (FL) enables distributed clients to train machine learning models collaboratively without sharing raw data. However, its scalability is hindered by client heterogeneity, ...
Abstract: Asynchronous Federated Learning (AFL) enhances the efficiency of edge collaborative learning systems by asynchronously aggregating client updates to prevent slowdowns from slow clients.
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