Trimming helps conformal prediction under contamination precisely when the anomaly score separates retention probabilities without biasing clean scores, otherwise the retained mixture coefficient prevents substantial decontamination.
The Annals of Mathematical Statistics , volume=
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A generalized Tweedie identity and moment-generating-function representation enable nonparametric recovery of full posteriors for heteroscedastic normal means with unknown variances without specifying a prior.
Exchangeable bootstrap combined with box calibration produces simultaneous confidence bands for the cumulative hazard that attain nominal asymptotic coverage and closer-to-nominal performance in simulations than prior methods.
citing papers explorer
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When Does Trimming Help Conformal Prediction? A Retained-Law Diagnostic under Calibration Contamination
Trimming helps conformal prediction under contamination precisely when the anomaly score separates retention probabilities without biasing clean scores, otherwise the retained mixture coefficient prevents substantial decontamination.
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Nonparametric f-Modeling for Empirical Bayes Inference with Unequal and Unknown Variances
A generalized Tweedie identity and moment-generating-function representation enable nonparametric recovery of full posteriors for heteroscedastic normal means with unknown variances without specifying a prior.
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Simultaneous confidence bands for cumulative hazard via exchangeable bootstrap and box calibration
Exchangeable bootstrap combined with box calibration produces simultaneous confidence bands for the cumulative hazard that attain nominal asymptotic coverage and closer-to-nominal performance in simulations than prior methods.