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arXiv · 2609.02880

Overcoming the Randomness-Utility Trade-off in Answering Differentially Private Linear Queries

Surendra Ghentiyala·Pritish Kamath·Ravi Kumar·Pasin Manurangsi
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Abstract

We study the question of answering linear queries with differential privacy using few (expected) random bits. We provide a randomness-efficient analog of the $\| \cdot \|_K$-norm mechanism of Hardt and Talwar [HT10]. For the $\ell_\infty$-error, our algorithm can answer $d$ linear queries with $O(d / \varepsilon)$ error using $O(\log d)$ random bits, improving upon algorithms of Canonne et al. and Ghentiyala [CSV25, Ghe26]; this is optimal when $\varepsilon \le 1/d$. We also provide a computationally efficient version of our algorithm, albeit with an $O(\log d)$ multiplicative increase in the error.

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Surendra Ghentiyala, Pritish Kamath, Ravi Kumar, Pasin Manurangsi. 2026-09-02. Overcoming the Randomness-Utility Trade-off in Answering Differentially Private Linear Queries. https://arxiv.org/abs/2609.02880

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