diffpriv 0.4.2
- Second vignette
bernstein on: Bernstein approximations
and use of DPMechBernstein for private function
release.
- Minor edits to docs
diffpriv 0.4.1
- Expanding test coverage of Bernstein mechanism and function
approximation code.
diffpriv 0.4.0
- Addition of
S3 constructor and predict()
generic implementation for fitting (non-iterated) Bernstein polynomial
function approximations.
- Addition of
DPMechBernstein class implementing the
Bernstein mechanism of Alda and Rubinstein (AAAI’2017), for privately
releasing functions.
- Bug fix in the Laplace random sampler affecting
DPMechLaplace
- Unit test coverage of new functionality; general documentation
improvements.
diffpriv 0.3.2
- Addition of
DPMechGaussian class for the generic
Gaussian mechanism to README, Vignette. Resolves #2
- Minor test additions.
diffpriv 0.3.1
- Refactoring around
releaseResponse() method in
DPMechNumeric. Resolves #1
- Increased test coverage.
diffpriv 0.3.0
- New
DPMechGaussian class implementing the Gaussian
mechanism, which achieves (epsilon,delta)-differential privacy by adding
Gaussian noise to numeric responses calibrated by L2-norm
sensitivity.
- Refactoring of
DPMechGaussian and
DPMechLaplace underneath a new VIRTUAL class
DPMechNumeric which contains common methods,
dims slot (formerly dim changed because
dim is a special slot for S4).
diffpriv 0.2.0
DPMechLaplace objects can now be initialized without
specifying non-private target response dim. In
such cases, the sensitivity sampler will perform an additional
target probe to determine dim.
diffpriv 0.1.0.901
- Sensitivity sampler methods no longer require oracles that return
lists. Acceptable oracles may now return lists, matrices, data frames,
numeric vectors, or char vectors. As a consequence some example code in
docs, README and vignette, is simplified.
diffpriv 0.1.0.900