William Sexton

According to our database, William Sexton authored at least 8 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Privately Answering Queries on Skewed Data via Per-Record Differential Privacy.

Jeremy Seeman, William Sexton, David Pujol, Ashwin Machanavajjhala

Proc. VLDB Endow., July, 2024

Slowly Scaling Per-Record Differential Privacy.

Brian Finley, Anthony M. Caruso, Justin C. Doty, Ashwin Machanavajjhala, Mikaela R. Meyer, David Pujol, William Sexton, Zachary Terner

CoRR, 2024

2022

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

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

CoRR, 2022

Bayesian and Frequentist Semantics for Common Variations of Differential Privacy: Applications to the 2020 Census.

Daniel Kifer, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Philip Leclerc, Ashwin Machanavajjhala, William Sexton, Pavel Zhuravlev

CoRR, 2022

The 2020 Census Disclosure Avoidance System TopDown Algorithm.

John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Micah Heineck, Christine Heiss, Robert Johns, Daniel Kifer, Philip Leclerc, Ashwin Machanavajjhala, Brett Moran, William Sexton, Matthew Spence, Pavel Zhuravlev

CoRR, 2022

2021

Differentially Private Algorithms for 2020 Census Detailed DHC Race \& Ethnicity.

Samuel Haney, William Sexton, Ashwin Machanavajjhala, Michael Hay, Gerome Miklau

CoRR, 2021

An Uncertainty Principle is a Price of Privacy-Preserving Microdata.

John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Simson L. Garfinkel, Daniel Kifer, Philip Leclerc, William Sexton, Ashley Simpson, Christine Task, Pavel Zhuravlev

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods.

John M. Abowd, Ian M. Schmutte, William Sexton, Lars Vilhuber

CoRR, 2019