Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13506)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Conference series link(s): BELIEF: International Conference on Belief Functions
Conference proceedings info: BELIEF 2022.
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Table of contents (29 papers)
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Front Matter
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Evidential Clustering
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Front Matter
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Machine Learning and Pattern Recognition
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Front Matter
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Algorithms and Evidential Operators
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Front Matter
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Data and Information Fusion
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Front Matter
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About this book
The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well-understood connections to other frameworks such as probability, possibility, and imprecise probability theories. It has been applied in diverse areas such as machine learning, information fusion, and pattern recognition.
The 29 full papers presented in this book were carefully selected and reviewed from 31 submissions. The papers cover a wide range on theoretical aspects on mathematical foundations, statistical inference as well as on applications in various areas including classification, clustering, data fusion, image processing, and much more.
Editors and Affiliations
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University of Paris-Saclay, Gif sur Yvette, France
Sylvie Le Hégarat-Mascle, Emanuel Aldea
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Sorbonne University, Paris, France
Isabelle Bloch
Bibliographic Information
Book Title: Belief Functions: Theory and Applications
Book Subtitle: 7th International Conference, BELIEF 2022, Paris, France, October 26–28, 2022, Proceedings
Editors: Sylvie Le Hégarat-Mascle, Isabelle Bloch, Emanuel Aldea
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-031-17801-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Softcover ISBN: 978-3-031-17800-9Published: 01 October 2022
eBook ISBN: 978-3-031-17801-6Published: 29 September 2022
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XI, 317
Number of Illustrations: 13 b/w illustrations, 40 illustrations in colour