Weisheng Zhao

PPGNN: Fast and Accurate Privacy-Preserving Graph Neural Network Inference via Parallel and Pipelined Arithmetic-and-Logic FHE Accelerator

2024

Graph Neural Networks (GNNs) are increasingly used in fields like social media and bioinformatics, promoting the prosperity of cloud-based GNN inference services. Nevertheless, data privacy becomes a critical issue when handling sensitive information. Fully Homomorphic …

GNNavigator: Towards Adaptive Training of Graph Neural Networks via Automatic Guideline Exploration

2024

Graph Neural Networks (GNNs) succeed significantly in many applications recently. However, balancing GNNs training runtime cost, memory consumption, and attainable accuracy for various applications is non-trivial. Previous training methodologies suffer from inferior adaptability and lack …