Conformal Poset Prediction for Label Ranking

MCML Authors

Yusuf Sale

→ Group Eyke Hüllermeier
 Artificial Intelligence and Machine Learning

Eyke Hüllermeier

Prof. Dr.

Core PI

Artificial Intelligence and Machine Learning

Abstract

In supervised label ranking, an input X $in$ X is associated with a ranking $Pi$ $in$ Sm of a fixed label set Y = {1,...,m} (Fürnkranz and Hüllermeier, 2010). Write a $succ$$pi$ b when $pi$ ranks a before b, and identify $pi$ with {(a,b): a $succ$$pi$ b}. A ranker typically returns one permutation $hat{sigma}(X)$. Such a point prediction suppresses uncertainty: a model may be confident that a precedes c while having little evidence for the comparison between a and b, adjacent in $hat{sigma}(X)$. A natural output is therefore a strict partial order, which asserts only selected pairwise preferences and leaves the remaining pairs incomparable1. Our goal is to predict an informative partial order R(x) whose asserted comparisons are simultaneously correct, that is, P{R(Xn+1) $subseteq$ $Pi$n+1} $geq$ 1 - $alpha$.

inproceedings SH26

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COPA 2026

15th Symposium on Conformal and Probabilistic Prediction with Applications. Mölndal, Sweden, Sep 02-04, 2026.

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Authors

Y. Sale • E. Hüllermeier

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Links

URL

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Research Area

 A3 | Computational Models