Genetic CFL: Optimization of Hyper-Parameters in Clustered Federated Learning
Shaashwat Agrawal,
Sagnik Sarkar,
Mamoun Alazab
et al.
Abstract:Federated learning (FL) is a distributed model for deep learning that integrates client-server architecture, edge computing, and real-time intelligence. FL has the capability of revolutionizing machine learning (ML) but lacks in the practicality of implementation due to technological limitations, communication overhead, non-IID (independent and identically distributed) data, and privacy concerns. Training a ML model over heterogeneous non-IID data highly degrades the convergence rate and performance. The exist… Show more
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