Baohao Zhuang

A federated graph learning method based on personalized prototype aggregation and structure-aware augmentation

Federated Graph Learning (FGL) enables privacy-preserving collaborative training of Graph Neural Networks (GNNs) across distributed clients. In practice, discrepancies in local class distributions and graph structures result in non-independent and identically distributed (non-IID) data across clients, while heterogeneo...