Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
Federated Learning (FL) is an emerging decentralized learning framework through which multiple clients can collaboratively train a learning model. However, a major obstacle that impedes the wide deployment of FL lies in massive communication traffic. To train high dimensional machine learning models (such as CNN models), heavy communication traffic can …