Clustered federated Multitask learning is introduced as an efficient technique when data is
unbalanced and distributed amongst clients in a non-independent and identically distributed …

Hierarchical Federated Learning (HFL) has emerged to overcome the shortcomings of
conventional Federated Learning (FL) due to communication obstacles between the end …

The constant surge in the traffic demand on cellular networks has led to continuous
expansion in network capacity in order to accommodate existing and new service demands …

We propose a novel energy-efficient controlled descent algorithm (EECDA) for over-the-air
computation-assisted federated learning. In EECDA, the computing devices transmit their …

This paper focuses on the implementation of Pareto optimal front (POF) with deep neural
networks (DNNs) for optimizing and integrating of radio frequency (RF) designs. POF …