Purifying Approximate Differential Privacy with Randomized Post-processing

Yingyu Lin, Erchi Wang, Yi-An Ma +1

We propose a framework to convert $(\epsilon ,\hat{I}´)$-approximate Differential Privacy (DP) mechanisms into $({\epsilon }^{\prime },0)$-pure DP mechanisms under certain conditions, a proce…