FedSynth: Gradient Compression via Synthetic Data in Federated Learning

Shengyuan Hu, Jack Goetz, Kshitiz Malik +3

Model compression is important in federated learning (FL) with large models to reduce communication cost. Prior works have been focusing on sparsification based compression that co…