Post-hoc conformal selection creates a path of selection sets with estimated false discovery proportions, enabling data-driven adaptive FDR control with average reliability guarantees via e-variables and e-BH.
ACS: An interactive framework for conformal selection
3 Pith papers cite this work. Polarity classification is still indexing.
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Derives simultaneous finite-sample distribution-free upper bounds on false discovery proportions for conformal p-values that hold for every possible rejection threshold.
GAIF dynamically adjusts testing thresholds with feedback for finite-sample FDR control in sequential settings and extends to conformal selection via feedback-driven model selection.
citing papers explorer
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Beyond Fixed False Discovery Rates: Post-Hoc Conformal Selection with E-Variables
Post-hoc conformal selection creates a path of selection sets with estimated false discovery proportions, enabling data-driven adaptive FDR control with average reliability guarantees via e-variables and e-BH.
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Everywhere Valid Bounds on False Discovery Proportions in Conformal Inference
Derives simultaneous finite-sample distribution-free upper bounds on false discovery proportions for conformal p-values that hold for every possible rejection threshold.
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Feedback-Enhanced Online Multiple Testing with Applications to Conformal Selection
GAIF dynamically adjusts testing thresholds with feedback for finite-sample FDR control in sequential settings and extends to conformal selection via feedback-driven model selection.