wgzhsh/bayesian-differential-privacy

Code for the paper "Bayesian Differential Privacy for Machine Learning"

Bayesian Differential Privacy

Code for the paper "Bayesian Differential Privacy for Machine Learning" (https://arxiv.org/pdf/1901.09697.pdf).

The main code for Bayesian accounant is located in bayesian_privacy_accounant.py. File scaled_renyi.py contains a function to compute scaled Renyi divergence of two Gaussian distributions with equal variances. In a similar fashion, functions for other distributions can be added to accomodate other privacy mechanisms. IPython notebooks implement experiments from the paper.

Citation

Please cite our paper if find the code helpful:

@inproceedings{triastcyn2020bayesian,
  author    = {Triastcyn, Aleksei and Faltings, Boi},
  title     = {Bayesian Differential Privacy for Machine Learning},
  booktitle = {International Conference on Machine Learning},
  year      = {2020}
}