sensitivityNorm

an object of class <code><a rd-options="" href="/link/DPMech-class?package=diffpriv&version=0.4.2" data-mini-rdoc="diffpriv::DPMech-class">DPMech-class</a></code>.

mechanism

Norm of a <code><a rd-options="" href="/link/DPMech-class?package=diffpriv&version=0.4.2" data-mini-rdoc="diffpriv::DPMech-class">DPMech-class</a></code>'s non-private <code>target</code> function
evaluated on two given databases <code>X1</code>, <code>X2</code>.

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.

Benjamin Rubinstein

diffpriv

Easy Differential Privacy

Francesco Ald<c3><a0>

sensitivityNorm function

an object of class <code><a rd-options='' href='DPMech-class'>DPMech-class</a></code>.

Norm of a <code><a rd-options='' href='DPMech-class'>DPMech-class</a></code>'s non-private <code>target</code> function
evaluated on two given databases <code>X1</code>, <code>X2</code>.

sensitivityNorm: `DPMech` sensitivity-inducing norm.

Description

Usage

Arguments