mlsanityData to 14 Oct 2026

Empirical Differential Privacy

arXiv 1910.12820 ↗First posted 28 Oct 2019cs.LG cs.CRcited by 2

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Abstract (arXiv)

We show how to achieve differential privacy with no or reduced added noise, based on the empirical noise in the data itself. Unlike previous works on noiseless privacy, the empirical viewpoint avoids making any explicit assumptions about the random process generating the data.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Oct 2019.

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2 papers.