Federated learning (FL) is a promising solution to privacy preservation for data-driven deep
learning … aerial vehicle (UAV)-assisted wireless networks is still challenging due to limited …

… The most basic wireless ad hoc federated learning. They exchange their models with each
… wireless ad hoc federated learning (WAFL) – a fully distributed cooperative machine learning …

… tion approach for on-device federated learning via over-the-air computation. To improve
the performance and the convergence rate for federated learning, we propose a joint device …

… , network pruning, into wireless federated learning (FL) system to mitigate the local computation
and communication bottlenecks. Firstly, the convergence rate and learning … the learning …

… , federated machine learning at the wireless network edge. Index Terms— Adaptive federated
learning, Lyapunov stochastic optimization, edge machine learning, resource allocation. …

… However, when performing machine learning on a large WMN, the learning time
increases … , we apply federated learning to machine learning and propose a machine-learningbased …

… To provide a feasible solution, a paradigm of federated learning-enabled intelligent F-RANs …
of federated learning in F-RANs. To support the implementation of federated learning, some …

… In this paper, the problem of audio semantic communication over wireless networks is … We
consider a spectrum resource-limited uplink wireless network to deploy an ASC system, which …

… wireless channels and limited wireless resources (ie, spectrum), deploying federated learning
(FL) over wireless networks … local models caused by imperfect wireless transmissions. We …

… communication resources in wireless networks. Besides, … a two-step federated learning
framework, robust federated … on-device machine learning in wireless communications. RFA is a …