2026
Federated Graph Learning via Structure-Aware Fusion Using a Kalman Framework with Learnable Dynamics
ICML 2026poster
Federated Graph Learning (FGL) enables collaborative training across distributed clients without sharing raw graph data. However, its performance is severely hindered by graph-specific heterogeneity arising from divergent node feature distributions and disparate graph structures. Existing FGL method…