A remarkable interest in machine learning-based schemes as key enablers for
nextgeneration intelligent wireless systems has been observed. Most of the existing learning …

The burgeoning advances in machine learning and wireless technologies are forging a new
paradigm for future networks, which are expected to possess higher degrees of intelligence …

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

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 …

The advances of both computation and communication technologies facilitate the
exploitation of massive data generated by mobile devices. It is attractive to leverage these …

Due to the increasing need for massive data analysis and machine learning model training
at the network edge, as well as the rising concerns about data privacy, a new distrib⁃ uted …

Motivated by ever-increasing computational resources at edge devices and increasing
privacy concerns, a new machine learning (ML) framework called federated learning (FL) …

To facilitate the deployment of machine learning in resource and privacy-constrained
systems such as the Internet of Things, federated learning (FL) has been proposed as a …

Federated learning (FL) is a privacy-preserving machine learning setting that enables many
devices to jointly train a shared global model without the need to reveal their data to a …

The explosive growth of smart devices (eg, mobile phones, vehicles, drones) with sensing,
communication, and computation capabilities gives rise to an unprecedented amount of …