Yangyi Liu

M22: Rate-Distortion Inspired Gradient Compression

In federated learning (FL), the communication constraint between the remote users and the Parameter Server (PS) is a crucial bottleneck. This paper proposes M22, a rate-distortion inspired approach to model update compression for distributed training of deep neural networks (DNNs). In particular, (i…