FDR control and FDP bounds for conformal link prediction

Fuente: arXiv
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Autores principales: Blanchard, Gilles, Durand, Guillermo, Marandon-Carlhian, Ariane, Périer, Romain
Formato: Preprint
Publicado: 2024
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author Blanchard, Gilles
Durand, Guillermo
Marandon-Carlhian, Ariane
Périer, Romain
author_facet Blanchard, Gilles
Durand, Guillermo
Marandon-Carlhian, Ariane
Périer, Romain
contents In Marandon (2023), the author introduces a procedure to detect true edges from a partially observed graph using a conformal prediction fashion: first computing scores from a trained function, deriving conformal p-values from them and finally applying a multiple testing procedure. In this paper, we prove that the resulting procedure indeed controls the FDR, and we also derive uniform FDP bounds, thanks to an exchangeability argument and the previous work of Marandon et al. (2022).
format Preprint
id arxiv_https___arxiv_org_abs_2404_02542
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle FDR control and FDP bounds for conformal link prediction
Blanchard, Gilles
Durand, Guillermo
Marandon-Carlhian, Ariane
Périer, Romain
Statistics Theory
In Marandon (2023), the author introduces a procedure to detect true edges from a partially observed graph using a conformal prediction fashion: first computing scores from a trained function, deriving conformal p-values from them and finally applying a multiple testing procedure. In this paper, we prove that the resulting procedure indeed controls the FDR, and we also derive uniform FDP bounds, thanks to an exchangeability argument and the previous work of Marandon et al. (2022).
title FDR control and FDP bounds for conformal link prediction
topic Statistics Theory
url https://arxiv.org/abs/2404.02542