论文标题

Tumult Analytics:一个可靠,易于使用,可扩展和表达性差异隐私的框架

Tumult Analytics: a robust, easy-to-use, scalable, and expressive framework for differential privacy

论文作者

Berghel, Skye, Bohannon, Philip, Desfontaines, Damien, Estes, Charles, Haney, Sam, Hartman, Luke, Hay, Michael, Machanavajjhala, Ashwin, Magerlein, Tom, Miklau, Gerome, Pai, Amritha, Sexton, William, Shrestha, Ruchit

论文摘要

在这篇简短的论文中,我们概述了Tumult Analytics的设计,这是美国人口普查局,Wikimedia基金会或国税局等机构使用的差异隐私框架。

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 Foundation, or the Internal Revenue Service.

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