10 citations · 25 across the 3 of their papers we have counts for
3 papers
Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy
Skye Berghel, Philip Bohannon, Damien Desfontaines +10
In this short paper, we outline the design of Tumult Analytics, a Python framework for differential privacy used at institutions such as the U.S. Census Bureau, the Wikimedia Found…
Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census
Daniel Kifer, John M. Abowd, Robert Ashmead +5
The purpose of this paper is to guide interpretation of the semantic privacy guarantees for some of the major variations of differential privacy, which include pure, approximate, R…
The 2020 Census Disclosure Avoidance System TopDown Algorithm
John M. Abowd, Robert Ashmead, Ryan Cumings-Menon +11
The Census TopDown Algorithm (TDA) is a disclosure avoidance system using differential privacy for privacy-loss accounting. The algorithm ingests the final, edited version of the 2…