Federated learning has been shown to be efficient for training a global model without
needing to collect all data from multiple entities to the centralized server. However, the …

Federated learning is a promising distributed learning paradigm for protecting data privacy
by delegating learning tasks to local clients and aggregating local models, instead of raw …

In this paper, we propose a multi-dimensional resource management scheme for Federated
Learning with non-independent and identically distributed (non-IID) data on battery-powered …

Recently, federated learning (FL) has gained considerable attention as a promising training
framework that effectively leverages distributed data and computational resources while …