FDR control and FDP bounds for conformal link prediction

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...

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Hauptverfasser:	Blanchard, Gilles, Durand, Guillermo, Marandon-Carlhian, Ariane, Périer, Romain
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Sprache:	eng
Schlagworte:	Mathematics - Statistics Theory Statistics - Theory
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creator	Blanchard, Gilles Durand, Guillermo Marandon-Carlhian, Ariane Périer, Romain
description	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).
doi_str_mv	10.48550/arxiv.2404.02542
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title	FDR control and FDP bounds for conformal link prediction
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