Cheng-Lu Pan

Towards Fair and Robust Graph Federated Learning via Incentive Mechanisms

Graph federated learning (FL) allows multiple agents to collaboratively train a global graph model while preserving data privacy. However, current methods overlook the issue of low-quality or malicious data contributions, which can degrade the global model’s performance. This paper addresses this gap by proposing a nov...