1.5k citations · 1.6k across the 6 of their papers we have counts for
4 papers · 1 filter
The Podium Mechanism: Improving on the Laplace and Staircase Mechanisms
Vasyl Pihur
The Podium mechanism guarantees ()-differential privacy by sampling noise from a \emph{finite} mixture of three uniform distributions. By carefully constructing such a mixtur…
Differentially-Private "Draw and Discard" Machine Learning
Vasyl Pihur, Aleksandra Korolova, Frederick Liu +4
In this work, we propose a novel framework for privacy-preserving client-distributed machine learning. It is motivated by the desire to achieve differential privacy guarantees in t…
Building a RAPPOR with the Unknown: Privacy-Preserving Learning of Associations and Data Dictionaries
Giulia Fanti, Vasyl Pihur, Úlfar Erlingsson
Techniques based on randomized response enable the collection of potentially sensitive data from clients in a privacy-preserving manner with strong local differential privacy guara…
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
Úlfar Erlingsson, Vasyl Pihur, Aleksandra Korolova
Randomized Aggregatable Privacy-Preserving Ordinal Response, or RAPPOR, is a technology for crowdsourcing statistics from end-user client software, anonymously, with strong privacy…