One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them

Saber Salehkaleybar, Arsalan Sharifnassab, S. Jamaloddin Golestani

We consider distributed statistical optimization in one-shot setting, where there are $m$ machines each observing $n$ i.i.d. samples. Based on its observed samples, each machine se…