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Kernel Mode Decomposition Programming by Owhadi Houman (23 results)
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Kernel Mode Decomposition and the Programming of Kernels
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Kernel Mode Decomposition and the Programming of Kernels
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Kernel Mode Decomposition and the Programming of Kernels (Surveys and Tutorials in the Applied Mathematical Sciences)
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Kernel Mode Decomposition and the Programming of Kernels
Published by Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Language: English
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Kernel Mode Decomposition and the Programming of Kernels
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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
Published by Springer, Berlin|Springer International Publishing|Springer, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Language: English
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
Published by Springer International Publishing, Springer Nature Switzerland Dez 2021, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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Taschenbuch. Condition: Neu. 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 128 pp. Englisch.
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Kernel Mode Decomposition and the Programming of Kernels
Published by Springer International Publishing, Springer International Publishing, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Language: English
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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Taschenbuch. Condition: Neu. Kernel Mode Decomposition and the Programming of Kernels | Houman Owhadi (u. a.) | Taschenbuch | x | Englisch | 2021 | Springer | EAN 9783030821708 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Kernel Mode Decomposition and the Programming of Kernels
Published by Springer Nature Switzerland AG, CH, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Language: English
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Add to basketPaperback. Condition: Brand New. 128 pages. 9.25x6.10x0.28 inches. In Stock. This item is printed on demand.
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Kernel Mode Decomposition and the Programming of Kernels
Published by Springer International Publishing Dez 2021, 2021
ISBN 10: 3030821706 ISBN 13: 9783030821708
Language: English
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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