Federated learning (FL) is an attractive paradigm for making use of rich distributed data
while protecting data privacy. Nonetheless, non-ideal communication links and limited …

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

For distributed learning among collaborative users, this paper develops and analyzes a
communication-efficient scheme for federated learning (FL) over the air, which incorporates …

This paper studies communication-efficient federated learning (FL) over the air, which is
based on 1-bit compressive sensing (CS) and analog aggregation transmissions. To …

The valuable data collected by IoT devices together with the resurgence of machine learning
(ML) stimulate the latest trend of artificial intelligence (AI) at the edge. However, traditional …

Realizing the distributed adaptive network construction of multi-UAV networks is an urgent
challenge, as they lack a reliable common control channel and can only maintain a limited …

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

In this paper, we study a communication-efficient distributed learning scheme through a
holistic integration of federated learning (FL) and particle swarm optimization, called DSL …

Distributed learning has attracted extensive interest in recent years, owing to the explosion
of data generated from mobile sensors, social media services, and other networked multi …

Since they can independently gather data from their surroundings, Wireless Sensor
Networks (WSNs) have garnered a lot of interest in many different contexts. However, the …