Proposing a decoupled framework for training GNN models with enhanced privacy-utility trade-off using DP-APPR algorithms.
Eclipse introduces a privacy-preserving GNN training algorithm that perturbs singular values, achieving strong privacy protection on edges while maintaining model utility.
Achieving node-level differential privacy for training GNNs with enhanced privacy-utility trade-off.