Emilio Luz-Ricca

Data-Free One-Shot Federated Learning Under Very High Statistical Heterogeneity

Federated learning (FL) is an emerging distributed learning framework that collaboratively trains a shared model without transferring the local clients' data to a centralized server. Motivated by concerns stemming from extended communication and potential attacks, one-shot FL limits communication to…