This repo adapts code from https://github.com/xiyangl3/adp-estimator/ to apply the techniques in that repo's accompanying paper, Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases to examining PyDP.

• To run the experiments, you need to have the following libraries installed:

1. python = 3.6
2. numpy
3. scipy

• The coefficient of best polynomial approximation are pre-computed and stored as ".mat" file. The coefficient of Chebyshev polynomials of the first kind are stored as ".npy" file.

• To get the coefficient of best polynomial approximation, you need to install Chebfun in Matlab through http:https://www.chebfun.org/

• To get the coefficient of Chebyshev polynomials, you need to install:

1. sympy

You are encouraged to cite orginal paper for acedamic research:

@inproceedings{liu2019minimax,
  title={Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases},
  author={Liu, Xiyang and Oh, Sewoong},
  booktitle={Advances in Neural Information Processing Systems},
  pages={2414--2425},
  year={2019}
}

MIT.