In this paper, the problem of training federated learning (FL) algorithms over a realistic
wireless network is studied. In particular, in the considered model, wireless users perform an …

In this article, the problem of training federated learning (FL) algorithms over a realistic
wireless network is studied. In the considered model, wireless users execute an FL …

In this paper, the convergence time of federated learning (FL), when deployed over a
realistic wireless network, is studied. In particular, with the considered model, wireless users …

In this paper, the convergence time of federated learning (FL), when deployed over a
realistic wireless network, is studied. In particular, a wireless network is considered in which …

Wireless federated learning (FL) is a collaborative machine learning (ML) framework in
which wireless client-devices independently train their ML models and send the locally …

In this paper, the problem of delay minimization for federated learning (FL) over wireless
communication networks is investigated. In the considered model, each user exploits limited …

There is an increasing interest in a fast-growing machine learning technique called
Federated Learning (FL), in which the model training is distributed over mobile user …

Federated learning (FL) over resource-constrained wireless networks has recently attracted
much attention. However, most existing studies consider one FL task in single-cell wireless …

Federated learning (FL) emerges as a distributed training method in the Internet of Things
(IoT), allowing participating clients to use their local data to train local models and upload …

Federated learning becomes increasingly attractive in the areas of wireless communications
and machine learning due to its powerful learning ability and potential applications. In …