2026
MV-FGAD: Towards Efficient and Effective Federated Graph Anomaly Detection via Multi-view Learning
ICML 2026oral
Federated graph anomaly detection (GAD) aims to identify abnormal nodes in distributed subgraphs through collaborative learning. However, existing methods suffer from two limitations. 1) Their reliance on neighborhood aggregation assumes that anomalous information can be sufficiently captured, which…