Universally Consistent Conformal Predictive Distributions

Vladimir Vovk

Universally Consistent Conformal Predictive Distributions

Vladimir Vovk

Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, PMLR 105:105-122, 2019.

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.

Cite this Paper

BibTeX


@InProceedings{pmlr-v105-vovk19a,
  title = 	 {Universally Consistent Conformal Predictive Distributions},
  author =       {Vovk, Vladimir},
  booktitle = 	 {Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications},
  pages = 	 {105--122},
  year = 	 {2019},
  editor = 	 {Gammerman, Alex and Vovk, Vladimir and Luo, Zhiyuan and Smirnov, Evgueni},
  volume = 	 {105},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {09--11 Sep},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v105/vovk19a/vovk19a.pdf},
  url = 	 {https://proceedings.mlr.press/v105/vovk19a.html},
  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.}
}

Endnote

%0 Conference Paper
%T Universally Consistent Conformal Predictive Distributions
%A Vladimir Vovk
%B Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications
%C Proceedings of Machine Learning Research
%D 2019
%E Alex Gammerman
%E Vladimir Vovk
%E Zhiyuan Luo
%E Evgueni Smirnov	
%F pmlr-v105-vovk19a
%I PMLR
%P 105--122
%U https://proceedings.mlr.press/v105/vovk19a.html
%V 105
%X 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.

APA


Vovk, V.. (2019). Universally Consistent Conformal Predictive Distributions. Proceedings of the Eighth Symposium on Conformal and Probabilistic Prediction and Applications, in Proceedings of Machine Learning Research 105:105-122 Available from https://proceedings.mlr.press/v105/vovk19a.html.

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