25th Estonian Winter School in Computer Science (EWSCS)
XXV Eesti Arvutiteaduse Talvekool

Palmse, Estonia, March 1 - 6, 2020

Marco Gaboardi

Department of Computer Science
Boston University

Differential privacy and applications


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

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