A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy

18 December 2023

Papers citing "A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy"

5 / 5 papers shown

Title
PFGuard: A Generative Framework with Privacy and Fairness Safeguards Soyeon Kim Yuji Roh Geon Heo Steven Euijong Whang 31 0 0 03 Oct 2024
A Private and Computationally-Efficient Estimator for Unbounded Gaussians Gautam Kamath Argyris Mouzakis Vikrant Singhal Thomas Steinke Jonathan R. Ullman 50 39 0 08 Nov 2021
Private sampling: a noiseless approach for generating differentially private synthetic data M. Boedihardjo Thomas Strohmer Roman Vershynin SyDa 27 14 0 30 Sep 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data Georgi Ganev Bristena Oprisanu Emiliano De Cristofaro 37 57 0 23 Sep 2021
Robust and Differentially Private Mean Estimation Xiyang Liu Weihao Kong Sham Kakade Sewoong Oh OOD FedML 37 75 0 18 Feb 2021