mlsanityData to 7 Oct 2026

The Test of Tests: A Framework For Differentially Private Hypothesis Testing

arXiv 2302.04260 ↗First posted 8 Feb 2023stat.ME cs.CR cs.LGcited by 9

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Abstract (arXiv)

We present a generic framework for creating differentially private versions of any hypothesis test in a black-box way. We analyze the resulting tests analytically and experimentally. Most crucially, we show good practical performance for small data sets, showing that at epsilon = 1 we only need 5-6 times as much data as in the fully public setting. We compare our work to the one existing framework of this type, as well as to several individually-designed private hypothesis tests. Our framework is higher power than other generic solutions and at least competitive with (and often better than) individually-designed tests.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 15 of its 44 references that are in the map. First posted on arXiv 8 Feb 2023.

Builds on

15 of 44 references.

References · 15

  1. 2015Differentially Private Ordinary Least Squarescited by 36
  2. 2018The Structure of Optimal Private Tests for Simple Hypothesescited by 26
  3. 2016Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testingcited by 24
  4. 2019Privacy-preserving parametric inference: a case for robust statisticscited by 17
  5. 2019Private Identity Testing for High-Dimensional Distributionscited by 15
  6. 2017Differentially private significance tests for regression coefficientscited by 12
  7. 2019Differentially Private Nonparametric Hypothesis Testingcited by 12
  8. 2022Private High-Dimensional Hypothesis Testingcited by 12
  9. 2017Priv'IT: Private and Sample Efficient Identity Testingcited by 10
  10. 2019Improved Differentially Private Analysis of Variancecited by 9
  11. 2022Hypothesis Testing for Differentially Private Linear Regressioncited by 7
  12. 2022Differentially Private Hypothesis Testing with the Subsampled and Aggregated Randomized Response Mechanismcited by 7
3 more
  1. 2018Comparing Population Means under Local Differential Privacy: with Significance and Powercited by 5
  2. 2017Differentially Private ANOVA Testingcited by 4
  3. 2017Differentially Private Regression for Discrete-Time Survival Analysiscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 3; 2025: 3; 2026: 2.

9 papers.

  1. 2024Robust Kernel Hypothesis Testing under Data Corruptioncited by 7
  2. 2024Differentially private Bayesian testscited by 1
  3. 2024Evasive Active Hypothesis Testing with Deep Neuroevolution: The Single- and Multi-Agent Casescited by 1
  4. 2025Fiducial Matching: Differentially Private Inference for Categorical Datacited by 1
  5. 2025DP-SPRT: Differentially Private Sequential Probability Ratio Testscited by 1
  6. 2025Differentially Private E-Valuescited by 1
  7. 2026Optimal Rates for Differentially Private Hypothesis Testing with E-valuescited by 1
  8. 2023Differentially Private Conditional Independence Testingcited by 0
  9. 2026Near-Optimal Private Tests for Simple and MLR Hypothesescited by 0