Reproduce “Pure Differentially Private Query Release via Laplace Input Smoothing” on OpenResearch

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About this paper

Zongrui Zou

The authors present a polynomial-time pure-DP mechanism for answering k bounded statistical queries on N records. It updates a weighted synthetic distribution by selecting poorly fit queries and uses rare input perturbations to smooth the full selection transcript. With probability at least 1−β, the maximum query error is at most a universal constant times min(1, the square root of log(2d/β) log(2k) divided by Nε).

Summary by alphaXiv.

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