In addition, we propose the entire graph node training (EGNT) process, optimizing parameters by treating each sample as a graph node for feature aggregation and information updating. Validation using ...

Differential privacy (DP) has seen immense applications in learning on tabular, image, and sequential data where instance-level privacy is concerned. In learning on graphs, contrastingly, works on ...