13 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 13 cited
Dynamic Graph Unlearning: A General and Efficient Post-Processing Method via Gradient Transformation
He Zhang, Bang Wu, Xiangwen Yang +3
Dynamic graph neural networks (DGNNs) have emerged and been widely deployed in various web applications (e.g., Reddit) to serve users (e.g., personalized content delivery) due to t…
cs.CR2023★ 2 cited
Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification
Bang Wu, Xingliang Yuan, Shuo Wang +3
The deployment of Graph Neural Networks (GNNs) within Machine Learning as a Service (MLaaS) has opened up new attack surfaces and an escalation in security concerns regarding model…
cs.LG2023★ 3 cited
GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks
Bang Wu, He Zhang, Xiangwen Yang +4
The emergence of Graph Neural Networks (GNNs) in graph data analysis and their deployment on Machine Learning as a Service platforms have raised critical concerns about data misuse…