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An implementation of major general-purpose mechanisms for privatizing statistics, models, and machine learners, within the framework of differential privacy of Dwork et al. (2006) <doi:10.1007/11681878_14>. Example mechanisms include the Laplace mechanism for releasing numeric aggregates, and the exponential mechanism for releasing set elements. A sensitivity sampler (Rubinstein & Alda, 2017) <arXiv:1706.02562> permits sampling target non-private function sensitivity; combined with the generic mechanisms, it permits turn-key privatization of arbitrary programs.

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conda 733.4 kB | noarch/r-diffpriv-0.4.2-r43h142f84f_0.tar.bz2  1 year and 4 days ago 18 main
conda 728.7 kB | noarch/r-diffpriv-0.4.2-r42h142f84f_0.tar.bz2  2 years and 6 months ago 50 main
conda 674.8 kB | noarch/r-diffpriv-0.4.2-r36h6115d3f_0.tar.bz2  4 years and 10 months ago 113 main

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