Produktbild: Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization

Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization

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Dedicated to the Memory of Teuvo Kohonen / Proceedings of the 14th International Workshop, WSOM+ 2022, Prague, Czechia, July 6-7,2022, Lecture Notes in Networks and Systems 533

ISBN: 3031154436
ISBN 13: 9783031154430
Herausgeber: Jan Faigl/Madalina Olteanu/Jan Drchal
Verlag: Springer Verlag GmbH
Umfang: xii, 119 S., 11 s/w Illustr., 34 farbige Illustr., 119 p. 45 illus., 34 illus. in color.
Erscheinungsdatum: 27.08.2022
Auflage: 1/2023
Produktform: Kartoniert
Einband: Kartoniert

In this collection, the reader can find recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. The collection is balanced in presenting novel theoretical contributions with applied results in traditional fields of SOMs, such as visualization problems and data analysis. Besides, the collection further includes less traditional deployments in trajectory clustering and recent results on exploiting quantum computation. The presented book is worth interest to data analysis and machine learning researchers and practitioners, specifically those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization.

Artikelnummer: 6351228 Kategorie:

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Springer Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

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