Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization: Dedicated to the Memory of Teuvo Kohonen / Proceedings of the 14th International Workshop, WSOM+ 2022, Prague, Czechia, July 6-7, 2022 (Volume 533)
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ISBN 10: 3031154436 ISBN 13: 9783031154430
Published by Springer Nature, 2022
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Soft cover
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2022. 1st ed. 2022. paperback. . . . . . Seller Inventory # V9783031154430
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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.
From the Back Cover: 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.
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Title: Advances in Self-Organizing Maps, Learning ...
Publisher: Springer Nature
Publication Date: 2022
Binding: Soft cover
Condition: New
Edition: 1st Edition
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Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (Paperback)
Published by
Springer International Publishing AG, Cham, 2022
ISBN 10: 3031154436
ISBN 13: 9783031154430
New
Paperback
First Edition
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. In this collection, the reader can nd 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 elds 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, specically those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization. In this collection, the reader can nd recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9783031154430
Quantity: 1 available
Stock Image
Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (Paperback)
Published by
Springer International Publishing AG, Cham, 2022
ISBN 10: 3031154436
ISBN 13: 9783031154430
New
Paperback
First Edition
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. In this collection, the reader can nd 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 elds 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, specically those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization. In this collection, the reader can nd recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9783031154430
Quantity: 1 available