Abstract: In federated learning, non-independently and non-identically distributed heterogeneous data on the clients can limit both the convergence speed and model utility of federated learning, and ...
Implementation of Federated Learning Algorithms for Non Independent and Identically Distributed Data
Abstract: Federated Learning (FL) has emerged as a transformative approach for training machine learning models across decentralized data sources while preserving privacy. This study evaluates the ...
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