Marco Gaboardi
Department of Computer Science
Boston University
USA
Differential privacy and applications
Abstract
Differential privacy offers ways to answer statistical queries about sensitive data while providing strong provable privacy guarantees ensuring that the presence or absence of a single individual in the data has a negligible statistical effect on the query's result.
In this class, I will first introduce the basic concepts of differential privacy and some of the fundamental mechanisms for building differentially private programs. Then, I will discuss several recently developed models for differential privacy in a multi-party setting. To conclude, I will discuss the relations of differential privacy with statistics, machine learning, and adaptive data analysis.
Course materials
- M. Gaboardi. Differential privacy and applications. Slides from EWSCS 2020.
- Videos from the lectures (large, unedited files) [mp4, password-protected]
Last changed
April 10, 2020 22:30 Europe/Helsinki (GMT +03:00)
by
local organizers, ewscs20(at)cs.ioc.ee
EWSCS'20 page:
//cs.ioc.ee/ewscs/2020/