A Joint Exponential Mechanism For Differentially Private Top-$k$
Cryptography and Security
2022-09-01 v2
Abstract
We present a differentially private algorithm for releasing the sequence of elements with the highest counts from a data domain of elements. The algorithm is a "joint" instance of the exponential mechanism, and its output space consists of all length- sequences. Our main contribution is a method to sample this exponential mechanism in time and space . Experiments show that this approach outperforms existing pure differential privacy methods and improves upon even approximate differential privacy methods for moderate .
Keywords
Cite
@article{arxiv.2201.12333,
title = {A Joint Exponential Mechanism For Differentially Private Top-$k$},
author = {Jennifer Gillenwater and Matthew Joseph and Andrés Muñoz Medina and Mónica Ribero},
journal= {arXiv preprint arXiv:2201.12333},
year = {2022}
}