An algorithm for private density estimation.
Julia
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README.md

README.md

Private Density Estimation

This package contains the algorithm and experiments for the following paper:

Differentially Private Learning of Structured Discrete Distributions
Ilias Diakonikolas, Moritz Hardt, Ludwig Schmidt
NIPS 2015

The code is written in Julia (v0.5). The script src/histogram_experiment.jl runs the experiments in the paper for synthetic distributions (mixtures of Gaussian, Beta, and Gamma distributions).

For an example of how to use the code, see the Jupyter notebook examples/histogram_approximation.ipynb.

The three plots above are generated in the notebook examples/website_plots.ipynb.