Nearly-Optimal Private Selection via Gaussian Mechanism

Fuente: arXiv
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Main Authors: Leeman, Ethan, Manurangsi, Pasin
Format: Preprint
Published: 2025
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author Leeman, Ethan
Manurangsi, Pasin
author_facet Leeman, Ethan
Manurangsi, Pasin
contents Steinke (2025) recently asked the following intriguing open question: Can we solve the differentially private selection problem with nearly-optimal error by only (adaptively) invoking Gaussian mechanism on low-sensitivity queries? We resolve this question positively. In particular, for a candidate set $\mathcal{Y}$, we achieve error guarantee of $\tilde{O}(\log |\mathcal{Y}|)$, which is within a factor of $(\log \log |\mathcal{Y}|)^{O(1)}$ of the exponential mechanism (McSherry and Talwar, 2007). This improves on Steinke's mechanism which achieves an error of $O(\log^{3/2} |\mathcal{Y}|)$.
format Preprint
id arxiv_https___arxiv_org_abs_2511_06871
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Nearly-Optimal Private Selection via Gaussian Mechanism
Leeman, Ethan
Manurangsi, Pasin
Cryptography and Security
Data Structures and Algorithms
Steinke (2025) recently asked the following intriguing open question: Can we solve the differentially private selection problem with nearly-optimal error by only (adaptively) invoking Gaussian mechanism on low-sensitivity queries? We resolve this question positively. In particular, for a candidate set $\mathcal{Y}$, we achieve error guarantee of $\tilde{O}(\log |\mathcal{Y}|)$, which is within a factor of $(\log \log |\mathcal{Y}|)^{O(1)}$ of the exponential mechanism (McSherry and Talwar, 2007). This improves on Steinke's mechanism which achieves an error of $O(\log^{3/2} |\mathcal{Y}|)$.
title Nearly-Optimal Private Selection via Gaussian Mechanism
topic Cryptography and Security
Data Structures and Algorithms
url https://arxiv.org/abs/2511.06871