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A Joint Exponential Mechanism for Differentially Private Top-k

Jenny Gillenwater
Monica Ribero Diaz
International Conference on Machine Learning (ICML) 2022
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Abstract

We present a differentially private algorithm for releasing the sequence of $k$ elements with the highest counts from a data domain of $d$ elements. The algorithm is a ``joint'' instance of the exponential mechanism, and its output space consists of all $O(d^k)$ length-$k$ sequences. Our main contribution is a method to sample this exponential mechanism in time $O(dk\log(k) + d\log(d))$ and space $O(dk)$. Experiments show that this approach outperforms existing pure differentially private methods and often improves upon even approximate differentially private methods for moderate $k$.