التفاصيل البيبلوغرافية
| العنوان: |
Integrative conformal p-values for out-of-distribution testing with labelled outliers. |
| المؤلفون: |
Liang, Ziyi1 (AUTHOR), Sesia, Matteo2 (AUTHOR) sesia@marshall.usc.edu, Sun, Wenguang3 (AUTHOR) |
| المصدر: |
Journal of the Royal Statistical Society: Series B (Statistical Methodology). Jul2024, Vol. 86 Issue 3, p671-693. 23p. |
| مصطلحات موضوعية: |
FALSE discovery rate |
| مستخلص: |
This paper presents a conformal inference method for out-of-distribution testing that leverages side information from labelled outliers, which are commonly underutilized or even discarded by conventional conformal p -values. This solution is practical and blends inductive and transductive inference strategies to adaptively weight conformal p -values, while also automatically leveraging the most powerful model from a collection of one-class and binary classifiers. Further, this approach leads to rigorous false discovery rate control in multiple testing when combined with a conditional calibration strategy. Extensive numerical simulations show that the proposed method outperforms existing approaches. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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