Lingcn: Structural linearized graph convolutional network for homomorphically encrypted inference
Abstract The growth of Graph Convolution Network (GCN) model sizes has revolutionized
numerous applications, surpassing human performance in areas such as personal …
numerous applications, surpassing human performance in areas such as personal …
Trustworthy graph neural networks: aspects, methods, and trends
Graph neural networks (GNNs) have emerged as a series of competent graph learning
methods for diverse real-world scenarios, ranging from daily applications such as …
methods for diverse real-world scenarios, ranging from daily applications such as …
Private Information Retrieval in Large Scale Public Data Repositories
The tutorial focuses on Private Information Retrieval (PIR), which allows clients to privately
query public or server-owned databases without disclosing their queries. The tutorial covers …
query public or server-owned databases without disclosing their queries. The tutorial covers …