no code implementations • 29 Oct 2021 • Cecilia Ferrando, Jennifer Gillenwater, Alex Kulesza
We argue that our mechanism is preferable to techniques that preserve the privacy of individuals by subsampling data proportionally to the privacy needs of users.
no code implementations • 14 Jun 2020 • Cecilia Ferrando, Shufan Wang, Daniel Sheldon
The goal of this paper is to develop a practical and general-purpose approach to construct confidence intervals for differentially private parametric estimation.
