Implementation of DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy

Accepted at 2024 ACM International World Wide Web Conference (WWW 24)

Install metis on mac:

1. Download metis-5.1.0.tar.gz from http://glaros.dtc.umn.edu/gkhome/metis/metis/download and unpack it
2. cd metis-5.1.0
3. make config shared=1
4. make install
5. export METIS_DLL=/usr/local/lib/libmetis.dylib

Package version:

tensorflow==1.15.4
networkx==2.5
metis==0.2a4
pynverse==0.1.4.4
scikit-learn==0.23.2
scipy==1.5.2
numba==0.51.2
numpy==1.18.5

Run main.py

bash script example

#!/bin/bash

alpha_list=(0.99)
topk_list=(4 8 16 32 64 128 256 512 1024)

for alpha_value in "${alpha_list[@]}"
do
	for topk_value in "${topk_list[@]}"
	do
 		python run_demo_test_noPowerInteration.py --lr 5e-4 --topk $topk_value --ntrain_div_classes 3754 --alpha $alpha_value
	done
done

Dataset options

1. Cora: data/cora_ml
2. Pubmed: data/pubmed
3. Ms academic: data/ms_academic
4. Facebook: data/facebook
5. pubmed: data/pubmed
6. Physics: data/physics