Abstract: Federated Learning (FL) enables distributed clients to train machine learning models collaboratively without sharing raw data. However, its scalability is hindered by client heterogeneity, ...

Abstract: Asynchronous Federated Learning (AFL) enhances the efficiency of edge collaborative learning systems by asynchronously aggregating client updates to prevent slowdowns from slow clients.

Every time I'm job hunting, I refresh my knowledge on the basics, because the theory tends to fade over time. Event loop almost always makes it onto my review list, since it's one of the most likely ...