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Multivariate Data Analysis on Matrix Manifolds: (with Manopt) (Springer Series in the Data Sciences) - Softcover
- PublisherSpringer
- Publication date2022
- ISBN 10 3030769763
- ISBN 13 9783030769765
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages472
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Multivariate Data Analysis on Matrix Manifolds
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Multivariate Data Analysis on Matrix Manifolds
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Multivariate Data Analysis on Matrix Manifolds
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Multivariate Data Analysis on Matrix Manifolds
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Multivariate Data Analysis on Matrix Manifolds : (with Manopt)
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Springer International Publishing, 2022
ISBN 10: 3030769763
ISBN 13: 9783030769765
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number ofexercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization. Seller Inventory # 9783030769765
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Multivariate Data Analysis on Matrix Manifolds: (with Manopt) (Springer Series in the Data Sciences)
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Multivariate Data Analysis on Matrix Manifolds: (with Manopt) (Springer Series in the Data Sciences)
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Multivariate Data Analysis on Matrix Manifolds: (with Manopt) (Springer Series in the Data Sciences)
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Multivariate Data Analysis on Matrix Manifolds
Published by
Springer International Publishing Sep 2022, 2022
ISBN 10: 3030769763
ISBN 13: 9783030769765
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Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization. 472 pp. Englisch. Seller Inventory # 9783030769765
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Multivariate Data Analysis on Matrix Manifolds
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Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10: 3030769763
ISBN 13: 9783030769765
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Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by . Seller Inventory # 693974418
Quantity: Over 20 available