mlsanityData to 14 Oct 2026

Testing Identity of Structured Distributions

arXiv 1410.2266 ↗First posted 8 Oct 2014cs.DS cs.IT math.ITcited by 19

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Abstract (arXiv)

We study the question of identity testing for structured distributions. More precisely, given samples from a em structured distribution q over [n] and an explicit distribution p over [n], we wish to distinguish whether q=p versus q is at least ε-far from p, in L1 distance. In this work, we present a unified approach that yields new, simple testers, with sample complexity that is information-theoretically optimal, for broad classes of structured distributions, including t-flat distributions, t-modal distributions, log-concave distributions, monotone hazard rate (MHR) distributions, and mixtures thereof.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Oct 2014.

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Citing papers per year: 2021: 3; 2022: 2; 2023: 5; 2024: 2; 2025: 3; 2026: 4.

19 papers.

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