Smart Cities sensing is an emerging paradigm to facilitate the transition into smart city
services. The advent of the Internet of Things (IoT) and the widespread use of mobile …

Federated learning is an emerging machine learning paradigm where clients train models
locally and formulate a global model based on the local model updates. To identify the state …

To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Abstract Federated Learning (FL), Artificial Intelligence (AI), and Explainable Artificial
Intelligence (XAI) are the most trending and exciting technology in the intelligent healthcare …

In this paper, we aim to make the best joint decision of device selection and computing and
spectrum resource allocation for optimizing federated learning (FL) performance 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 …

In this paper, the problem of energy efficient transmission and computation resource
allocation for federated learning (FL) over wireless communication networks is investigated …

In federated learning (FL), devices contribute to the global training by uploading their local
model updates via wireless channels. Due to limited computation and communication …

This paper studies federated learning (FL) in a classic wireless network, where learning
clients share a common wireless link to a coordinating server to perform federated model …

Federated Learning is a machine learning scheme in which a shared prediction model can
be collaboratively learned by a number of distributed nodes using their locally stored data. It …