pith. sign in

arxiv: 1603.04416 · v2 · pith:BEQY3BD6new · submitted 2016-03-14 · 💻 cs.LG

Criteria of efficiency for conformal prediction

Vladimir Vovk , Ilia Nouretdinov , Valentina Fedorova , Ivan Petej , Alex Gammerman This is my paper
classification 💻 cs.LG
keywords criteriaefficiencyconformalpredictionclassificationprobabilisticbinarycall
0
0 comments X p. Extension
pith:BEQY3BD6 Add to your LaTeX paper What is a Pith Number? 
\usepackage{pith}
\pithnumber{BEQY3BD6}

Prints a linked pith:BEQY3BD6 badge after your title and writes the identifier into PDF metadata. Compiles on arXiv with no extra files. Learn more

read the original abstract

We study optimal conformity measures for various criteria of efficiency of classification in an idealised setting. This leads to an important class of criteria of efficiency that we call probabilistic; it turns out that the most standard criteria of efficiency used in literature on conformal prediction are not probabilistic unless the problem of classification is binary. We consider both unconditional and label-conditional conformal prediction.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Uncertainty-Aware Transformers: Conformal Prediction for Language Models

    cs.LG 2026-04 unverdicted novelty 5.0

    CONFIDE applies conformal prediction to transformer embeddings for valid prediction sets, improving accuracy up to 4.09% and efficiency over baselines on models like BERT-tiny.