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Multivariate Data Analysis on Matrix Manifolds: (with Manopt) (Springer Series in the Data Sciences) - Hardcover
- VerlagSpringer-Verlag GmbH
- Erscheinungsdatum2021
- ISBN 10 3030769739
- ISBN 13 9783030769734
- EinbandTapa dura
- SpracheEnglisch
- Auflage1
- Anzahl der Seiten472
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Multivariate Data Analysis on Matrix Manifolds
Verlag:
Springer Nature Switzerland AG, 2021
ISBN 10: 3030769739
ISBN 13: 9783030769734
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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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Hardcover. Zustand: Brand New. 450 pages. 9.75x6.50x1.00 inches. In Stock. Artikel-Nr. __3030769739
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Multivariate Data Analysis on Matrix Manifolds : (with Manopt)
Verlag:
Springer International Publishing, 2021
ISBN 10: 3030769739
ISBN 13: 9783030769734
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Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Buch. Zustand: 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. Artikel-Nr. 9783030769734
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Multivariate Data Analysis on Matrix Manifolds
ISBN 10: 3030769739
ISBN 13: 9783030769734
Neu
Hardcover
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Zustand: New. 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.This graduate-level textbook aims to give a unified p. Artikel-Nr. 467591450
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