mlsanityData to 7 Oct 2026

On Differentially Private Counting on Trees

arXiv 2212.11967 ↗First posted 22 Dec 2022cs.DS cs.CRcited by 7

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Abstract (arXiv)

We study the problem of performing counting queries at different levels in hierarchical structures while preserving individuals' privacy. Motivated by applications, we propose a new error measure for this problem by considering a combination of multiplicative and additive approximation to the query results. We examine known mechanisms in differential privacy (DP) and prove their optimality, under this measure, in the pure-DP setting. In the approximate-DP setting, we design new algorithms achieving significant improvements over known ones.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Dec 2022.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 2; 2025: 0; 2026: 3.

7 papers.