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Kernel Mode Decomposition Programming by Owhadi Houman (16 results)
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Kernel Mode Decomposition and the Programming of Kernels (Surveys and Tutorials in the Applied Mathematical Sciences)
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesUS$ 86.59
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesUS$ 133.37
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Add to basketPaperback. Condition: Brand New. 128 pages. 9.25x6.10x0.28 inches. In Stock.
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesLanguage: English
Published by Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Condition: New. This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes.This monograph demonstrates a new approach to the classical .
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesLanguage: English
Published by Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes. The presentation includes a review of generalized additive models, additive kernels/Gaussian processes, generalized Tikhonov regularization, empirical mode decomposition, and Synchrosqueezing, which are all related to and generalizable under the proposed framework.Although kernel methods have strong theoretical foundations, they require the prior selection of a good kernel. While the usual approach to this kernel selection problem is hyperparameter tuning, the objective of this monograph is to present an alternative (programming) approach to the kernel selection problem while using mode decomposition as a prototypical pattern recognition problem. In this approach, kernels are programmed for the task at hand through the programming of interpretable regression networks in the contextof additive Gaussian processes.It is suitable for engineers, computer scientists, mathematicians, and students in these fields working on kernel methods, pattern recognition, and mode decomposition problems.
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Condition: new. Questo è un articolo print on demand.
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesLanguage: English
Published by Springer International Publishing Dez 2021, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes. The presentation includes a review of generalized additive models, additive kernels/Gaussian processes, generalized Tikhonov regularization, empirical mode decomposition, and Synchrosqueezing, which are all related to and generalizable under the proposed framework.Although kernel methods have strong theoretical foundations, they require the prior selection of a good kernel. While the usual approach to this kernel selection problem is hyperparameter tuning, the objective of this monograph is to present an alternative (programming) approach to the kernel selection problem while using mode decomposition as a prototypical pattern recognition problem. In this approach, kernels are programmed for the task at hand through the programming of interpretable regression networks in the contextof additive Gaussian processes.It is suitable for engineers, computer scientists, mathematicians, and students in these fields working on kernel methods, pattern recognition, and mode decomposition problems. 128 pp. Englisch.
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Kernel Mode Decomposition and the Programming of Kernels (Surveys and Tutorials in the Applied Mathematical Sciences)
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesUS$ 124.19
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Kernel Mode Decomposition and the Programming of Kernels
Book 9 of 9: Surveys and Tutorials in the Applied Mathematical SciencesLanguage: English
Published by Springer, Palgrave Macmillan Dez 2021, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This monograph demonstrates a new approach to the classical mode decomposition problem through nonlinear regression models, which achieve near-machine precision in the recovery of the modes. The presentation includes a review of generalized additive models, additive kernels/Gaussian processes, generalized Tikhonov regularization, empirical mode decomposition, and Synchrosqueezing, which are all related to and generalizable under the proposed framework.Although kernel methods have strong theoretical foundations, they require the prior selection of a good kernel. While the usual approach to this kernel selection problem is hyperparameter tuning, the objective of this monograph is to present an alternative (programming) approach to the kernel selection problem while using mode decomposition as a prototypical pattern recognition problem. In this approach, kernels are programmed for the task at hand through the programming of interpretable regression networks in the contextof additive Gaussian processes.It is suitable for engineers, computer scientists, mathematicians, and students in these fields working on kernel methods, pattern recognition, and mode decomposition problems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.
