Abstract: Hierarchical federated learning has emerged as a pragmatic approach to addressing scalability, robustness, and privacy concerns within distributed machine learning, particularly in the ...
Abstract: As a privacy-preserved distributed machine learning paradigm, federated edge learning (FEL) was designed to absorb knowledge from user devices to construct intelligent services without ...
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