Federated learning (FL) is an emerging decentralized machine learning framework enabling
private global model training by collaboratively leveraging local client data without …

In many federated learning (FL) models, a common strategy employed to ensure the
progress in the training process, is to wait for at least $ M $ clients out of the total $ N …

Federated learning (FL) is a distributed paradigm for collaboratively learning models without
having clients disclose their private data. One natural and practically relevant metric to …

Federated edge learning (FEEL) is gaining increasing attention due to its characteristics of
privacy protection, low latency, and low communication overhead. However, it still faces …

Coded machine learning is a technique to use codes, such as-maximum-distance-separable
(-MDS) codes, to reduce the negative effect of stragglers by requiring out of workers to …