A key assumption in most existing works on FL algorithms' convergence
an...
To lower the communication complexity of federated min-max learning, a
n...
Small lesions in magnetic resonance imaging (MRI) images are crucial for...
Federated learning (FL) has received a surge of interest in recent years...
Over-the-air federated learning (OTA-FL) has emerged as an efficient
mec...
This paper considers over-the-air federated learning (OTA-FL). OTA-FL
ex...
Present-day federated learning (FL) systems deployed over edge networks ...
Federated Learning (FL) refers to the paradigm where multiple worker nod...
Federated learning (FL) is a prevailing distributed learning paradigm, w...
Federated learning (FL) is a distributed machine learning architecture t...
In this work, we consider the resilience of distributed algorithms based...