Abstract: Federated learning (FL) is a distributed machine learning (ML) paradigm designed for numerous networked devices. To face the massive data generated by devices and privacy concerns in model ...

Abstract: In environments rich in data, machine learning models often encounter challenges such as data sparsity and overfitting, primarily due to datasets with an excessive number of features. To ...