26
Jun
Colloquium
The Complexities of Differential Privacy for Survey Data
Jörg Drechsler, LMU Munich
26.06.2024
4:15 pm - 5:45 pm
LMU Department of Statistics and via zoom
The concept of differential privacy gained substantial attention in recent years, most notably since the U.S. Census Bureau announced the adoption of the concept for the 2020 Decennial Census. However, despite its attractive theoretical properties, implementing the approach in practice is challenging, especially when it comes to survey data.
In this talk I will present some results from a project funded by the U.S. Census Bureau that explores the possibilities and limitations of differential privacy for survey data. I will highlight some key findings from the project and also discuss some of the challenges that would still need to be addressed if the framework should become the new data protection standard at statistical agencies.
Related
Colloquium • 05.02.2025 • LMU Department of Statistics and via zoom
TBA
Colloquium at the LMU Department of Statistics with Isabel Valera (Saarland University in Saarbrücken).
Colloquium • 29.01.2025 • LMU Department of Statistics and via zoom
TBA
Colloquium at the LMU Department of Statistics with Sophie Langer (University of Twente).
Colloquium • 15.01.2025 • LMU Department of Statistics and via zoom
TBA
Colloquium at the LMU Department of Statistics with Sonja Greven (HU Berlin).
Colloquium • 11.12.2024 • LMU Department of Statistics and via zoom
TBA
Colloquium at the LMU Department of Statistics with Stijn Vansteelandt (Ghent University).
Munich AI Lectures • 25.11.2024 • Große Aula der LMU Geschwister-Scholl-Platz 1, Room 120 80539 München
The Mathematical Universe behind Deep Neural Networks
Join us on Nov 25 for Prof. Helmut Bölcskei’s lecture on the mathematical foundations driving deep neural networks, hosted by Bavarian AI at LMU.