Federated learning (FL) is a popular privacy-preserving distributed training scheme, where
multiple devices collaborate to train machine learning models by uploading local model …

Model averaging is a widely adopted technique in federated learning (FL) that aggregates
multiple client models to obtain a global model. Remarkably, model averaging in FL yields a …

Federated learning (FL) enables edge devices to collaboratively train machine learning
models, with model communication replacing direct data uploading. While over-the-air …

Federated learning (FL) has attracted vivid attention as a privacy-preserving distributed
learning framework. In this work, we focus on cross-silo FL, where clients become the model …

Federated learning (FL) is an emerging distributed training scheme where edge devices
collaboratively train a model by uploading model updates instead of private data. To …

The 6G mobile networks are differentiated from 5G by two new usage scenarios-distributed
sensing and edge AI. Their natural integration, termed integrated sensing and edge AI …