Relational ⋆⋆\star-Liftings for Differential Privacy

@article{Barthe2019RelationalF,
  title={Relational ⋆⋆\star-Liftings for Differential Privacy},
  author={Gilles Barthe and Thomas Espitau and Justin Hsu and Tetsuya Sato and Pierre-Yves Strub},
  journal={Log. Methods Comput. Sci.},
  year={2019},
  volume={15}
}
Recent developments in formal verification have identified approximate liftings (also known as approximate couplings) as a clean, compositional abstraction for proving differential privacy. This construction can be defined in two styles. Earlier definitions require the existence of one or more witness distributions, while a recent definition by Sato uses universal quantification over all sets of samples. These notions have each have their own strengths: the universal version is more general… 

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