… —Federated learning (FL) has recently become one of the hottest focuses in wireless edge
… In FL, UEs train local machine learning models and transmit them to an aggregator, where a …

… of machine learning algorithms, 5G and beyond (5G+) wireless communications, and artificial
intelligence (AI) hardware implementation hastens the birth of federated learning (FL) over …

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

… 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 …

… Federated learning [6, 12] is a collaborative machine learning framework that requires no …
Federated learning aims to build machine learning models based on datasets stored locally …

… wireless aspect of FL, while also shedding light on the future research directions of wireless
federated learning … on the performance of the utilized wireless communication network, while …

… consider a split federated learning (SFL) framework that combines the parallel model training
mechanism of federated learning (FL) and the model splitting structure of split learning (SL)…

… the learning This article has been accepted for publication in IEEE Transactions on Wireless
Communications. This … Simeone, “Privacy for free: Wireless federated learning via uncoded …

The newly emerging federated learning (FL) framework offers a new way to train machine
learning models in a privacy-preserving manner. However, traditional FL algorithms are based …

… federated learning (FL) in a classic wireless network, where learning clients share a common
wireless link to a coordinating server to perform federated model training using their local …