22 citations · 22 across the 1 of their papers we have counts for
4 papers
Privacy Amplification by Mixing and Diffusion Mechanisms
Borja Balle, Gilles Barthe, Marco Gaboardi +1
A fundamental result in differential privacy states that the privacy guarantees of a mechanism are preserved by any post-processing of its output. In this paper we investigate unde…
Profile-Based Privacy for Locally Private Computations
Joseph Geumlek, Kamalika Chaudhuri
Differential privacy has emerged as a gold standard in privacy-preserving data analysis. A popular variant is local differential privacy, where the data holder is the trusted curat…
Rényi Differential Privacy Mechanisms for Posterior Sampling
Joseph Geumlek, Shuang Song, Kamalika Chaudhuri
Using a recently proposed privacy definition of Rényi Differential Privacy (RDP), we re-examine the inherent privacy of releasing a single sample from a posterior distribution. We…
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis
James Foulds, Joseph Geumlek, Max Welling +1
Bayesian inference has great promise for the privacy-preserving analysis of sensitive data, as posterior sampling automatically preserves differential privacy, an algorithmic notio…