Learning From Drift: Federated Learning on Non-IID Data via Drift Regularization

Yeachan Kim, Bonggun Shin

Federated learning algorithms perform reasonably well on independent and identically distributed (IID) data. They, on the other hand, suffer greatly from heterogeneous environments…