We propose a novel communication design, termed random orthogonalization, for federated
learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system. The …

This paper explores constrained non-convex personalized federated learning (PFL), in
which a group of workers train local models and a global model, under the coordination of a …

This paper investigates personalized federated learning, in which a group of workers are
coordinated by a server to train correlated local models, in addition to a common global …

Federated learning (FL) has been introduced to enable a large number of clients, possibly
mobile devices, to collaborate on generating a generalized machine learning model thanks …

Abstract Multi-Server Federated Learning (MSFL) is a decentralised way to train a global
model, taking a significant step toward enhanced privacy preservation while minimizing …