A central challenge in training classification models in the real-world federated system is learning with non-IID data. To cope with this, most of the existing works involve enforcing regularization in local optimization or improving the model aggregation scheme at the server.

In general, interventional data, i.e., data collected after a perturbation in

Figure 1: Illustration given, depicted and (ii) red/pink.