Universally consistent conformal predictive distributions. / Vovk, Vladimir.

Proceedings of Machine Learning Research. ed. / Alex Gammerman; Vladimir Vovk; Zhiyuan Luo; Evgueni Smirnov. Vol. 105 2019. p. 105-122.

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Abstract

This paper describes conformal predictive systems that are universally consistent in the sense of being consistent under any data-generating distribution, assuming that the observations are produced independently in the IID fashion. Being conformal, these predictive systems satisfy a natural property of small-sample validity, namely they are automatically calibrated in probability.
Original languageEnglish
Title of host publicationProceedings of Machine Learning Research
EditorsAlex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni Smirnov
Pages105-122
Number of pages18
Volume105
Publication statusPublished - 29 Aug 2019
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 34498216