Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data

Tailin Zhou, Zehong Lin, Jun Zhang +1

Model averaging is a widely adopted technique in federated learning (FL) that aggregates multiple client models to obtain a global model. Remarkably, model averaging in FL yields a…