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New 'cheap permutation testing' method accelerates statistical analysis

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel method called "cheap permutation testing" to significantly accelerate statistical tests for distinguishing distributions and testing independence. This approach involves grouping data points into bins and permuting only these bins, rather than individual data points. The method offers substantial speed improvements while retaining the exact false positive control and minimax optimality of standard permutation tests. Experiments demonstrate its effectiveness across various statistical tests, including MMD, HSIC, and Wilcoxon-Mann-Whitney. AI

IMPACT This method could improve the efficiency of machine learning model evaluations and data analysis pipelines.

RANK_REASON Academic paper detailing a new statistical method. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New 'cheap permutation testing' method accelerates statistical analysis

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Academic paper detailing a new statistical method. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey ·

    Cheap Permutation Testing

    arXiv:2502.07672v3 Announce Type: replace-cross Abstract: Permutation tests are a popular choice for distinguishing distributions and testing independence, due to their exact, finite-sample control of false positives and their minimax optimality when paired with U-statistics. How…

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