The next-generation of wireless networks will enable many machine learning (ML) tools and
applications to efficiently analyze various types of data collected by edge devices for …

Federated Learning is a much-needed technology in this golden era of big data and Artificial
Intelligence, due to its vital role in preserving data privacy, and eliminating the need to …

Metaverse is envisioned to merge the actual world with a virtual world to bring users
unprecedented immersive feelings. To ensure user experience, federated learning (FL) has …

Over-the-air federated edge learning (Air-FEEL) has emerged as a communication-efficient
solution to enable distributed machine learning over edge devices by using their data locally …

This article studies decentralized federated learning algorithms in wireless IoT networks.
The traditional parameter server architecture for federated learning faces some problems …

As a promising distributed learning technology, analog aggregation-based federated
learning over the air (FLOA) provides high communication efficiency and privacy …

The rapid growth of Internet of Things (IoT) has led to the widespread deployment of smart
IoT devices at the wireless edge for collaborative machine learning tasks, ushering in a new …

Federated learning (FL) is a framework for realizing distributed machine learning in an
environment where training samples are distributed to each device. Recently, FL has …

In this paper, a new communication-efficient federated learning (FL) framework is proposed,
inspired by vector quantized compressed sensing. The basic strategy of the proposed …

Federated learning (FL) is a popular distributed learning framework that is proposed to
address privacy concerns in traditional machine learning. However, recent research has …