M22: A Communication-Efficient Algorithm for Federated Learning Inspired by Rate-Distortion

Yangyi Liu, Stefano Rini, Sadaf Salehkalaibar +1

In federated learning (FL), the communication constraint between the remote learners and the Parameter Server (PS) is a crucial bottleneck. For this reason, model updates must be c…