Foreword to this special issue: conformal and probabilistic prediction with applications

Foreword to this special issue: conformal and probabilistic prediction with applications Ann Math Artif Intell (2017) 81:1–2 DOI 10.1007/s10472-017-9557-7 Foreword to this special issue: conformal and probabilistic prediction with applications 1 1 Alexander Gammerman · Vladimir Vovk Published online: 8 July 2017 © Springer International Publishing AG 2017 This issue of the Annals of Mathematics and Artificial Intelligence is devoted to conformal prediction, a modern machine learning technique that provides predictions and well- calibrated measures of confidence for individual observations without assuming anything more than that the data are generated independently from the same probability distribution. Most of the papers in this issue have been selected from the Fifth Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in April 2016 at the Cen- tro de Investigaciones Energeticas, ´ Medioambientales y Tecnologicas ´ (CIEMAT), Madrid, Spain. The first Special Issue of this journal devoted to conformal prediction was published in 2015 (Volume 74, Issues 1–2); most of the papers included in that Special Issue were selected from those presented at the First Symposium in the COPA series, held in 2012 in Greece. This new Special Issue summarises the progress of the method of conformal prediction in theory and applications. Its full title is now slightly longer, including the http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Mathematics and Artificial Intelligence Springer Journals

Foreword to this special issue: conformal and probabilistic prediction with applications

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Publisher
Springer International Publishing
Copyright
Copyright © 2017 by Springer International Publishing AG
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Mathematics, general; Computer Science, general; Complex Systems
ISSN
1012-2443
eISSN
1573-7470
D.O.I.
10.1007/s10472-017-9557-7
Publisher site
See Article on Publisher Site

Abstract

Ann Math Artif Intell (2017) 81:1–2 DOI 10.1007/s10472-017-9557-7 Foreword to this special issue: conformal and probabilistic prediction with applications 1 1 Alexander Gammerman · Vladimir Vovk Published online: 8 July 2017 © Springer International Publishing AG 2017 This issue of the Annals of Mathematics and Artificial Intelligence is devoted to conformal prediction, a modern machine learning technique that provides predictions and well- calibrated measures of confidence for individual observations without assuming anything more than that the data are generated independently from the same probability distribution. Most of the papers in this issue have been selected from the Fifth Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in April 2016 at the Cen- tro de Investigaciones Energeticas, ´ Medioambientales y Tecnologicas ´ (CIEMAT), Madrid, Spain. The first Special Issue of this journal devoted to conformal prediction was published in 2015 (Volume 74, Issues 1–2); most of the papers included in that Special Issue were selected from those presented at the First Symposium in the COPA series, held in 2012 in Greece. This new Special Issue summarises the progress of the method of conformal prediction in theory and applications. Its full title is now slightly longer, including the

Journal

Annals of Mathematics and Artificial IntelligenceSpringer Journals

Published: Jul 8, 2017

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