Optimal Differentially Private Sampling of Unbounded Gaussians

Valentio Iverson; Gautam Kamath; Argyris Mouzakis

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arXiv · 2503.01766

Optimal Differentially Private Sampling of Unbounded Gaussians

Valentio Iverson·Gautam Kamath·Argyris Mouzakis

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Abstract

We provide the first $\widetilde{\mathcal{O}}\left(d\right)$-sample algorithm for sampling from unbounded Gaussian distributions under the constraint of $\left(\varepsilon, \delta\right)$-differential privacy. This is a quadratic improvement over previous results for the same problem, settling an open question of Ghazi, Hu, Kumar, and Manurangsi.

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Valentio Iverson, Gautam Kamath, Argyris Mouzakis. 2025-03-03. Optimal Differentially Private Sampling of Unbounded Gaussians. https://arxiv.org/abs/2503.01766

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