Efficient Replay in Federated Incremental Learning Study

The authors propose Re-Fed, a framework for Federated Incremental Learning, to address catastrophic forgetting with data heterogeneity. Re-Fed efficiently discovers important samples for replay, improving model accuracy compared to state-of-the-art methods.