conda create -n RKHS-private-database python=3.6.3 matplotlib=2.1.0 numpy=1.13.3 pytorch=0.2.0 scikit-learn=0.19.0
source activate RKHS-private-database

python data.py 100000 2
python data.py 100000 5

python experiments.py ../data/mixture_of_Gaussians_N100000_D2 leak --M 10000 1
python experiments.py ../data/mixture_of_Gaussians_N100000_D5 leak --M 10000 1

python plot.py --alg1 ../results/D2_alg1_leak_M10000.json --path_save ../figures/leaksD2
python plot.py --alg1 ../results/D5_alg1_leak_M10000.json --path_save ../figures/leaksD5

python experiments.py ../data/mixture_of_Gaussians_N100000_D2 random --M 10000 1
python experiments.py ../data/mixture_of_Gaussians_N100000_D5 random --M 10000 1
python experiments.py ../data/mixture_of_Gaussians_N100000_D2 random --M 10000 2
python experiments.py ../data/mixture_of_Gaussians_N100000_D5 random --M 10000 2

python plot.py --alg1 ../results/D2_alg1_random_M10000.json --alg2 ../results/D2_alg2_random_M10000.json --path_save ../figures/nodataD2
python plot.py --alg1 ../results/D5_alg1_random_M10000.json --alg2 ../results/D5_alg2_random_M10000.json --path_save ../figures/nodataD5

@inproceedings{balog2018privacy,
  author = {Balog, Matej and Tolstikhin, Ilya and Sch\"olkopf, Bernhard},
  title = {Differentially {Private} {Database} {Release} via {Kernel} {Mean} {Embeddings}},
  booktitle = {35th International Conference on Machine Learning (ICML)},
  year = {2018},
  month = {July}
}