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Bayesian Tensor Decomposition for Signal Processing and Machine Learning: Modeling, Tuning-free Algorithms, and Applications - Couverture rigide
Synopsis
This book presents recent advances of Bayesian inference in structured tensor decompositions. It explains how Bayesian modeling and inference lead to tuning-free tensor decomposition algorithms, which achieve state-of-the-art performances in many applications, including
- blind source separation;
- social network mining;
- image and video processing;
- array signal processing; and,
- wireless communications.
The book begins with an introduction to the general topics of tensors and Bayesian theories. It then discusses probabilistic models of various structured tensor decompositions and their inference algorithms, with applications tailored for each tensor decomposition presented in the corresponding chapters. The book concludes by looking to the future, and areas where this research can be further developed.
Bayesian Tensor Decomposition for Signal Processing and Machine Learning is suitable for postgraduates and researchers with interests in tensor data analytics and Bayesian methods.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer International Publishing AG
- Date d'édition2023
- ISBN 10 303122437X
- ISBN 13 9783031224379
- ReliureRelié
- Langueanglais
- Nombre de pages183
- Coordonnées du fabricantnon disponible
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning
Vendeur : Basi6 International, Irving, TX, Etats-Unis
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning
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Springer, Berlin|Springer International Publishing|Springer, 2023
ISBN 10 : 303122437X
ISBN 13 : 9783031224379
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents recent advances of Bayesian inference in structured tensor decompositions. It explains how Bayesian modeling and inference lead to tuning-free tensor decomposition algorithms, which achieve state-of-the-art performances in many applicatio. N° de réf. du vendeur 748634232
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning: Modeling, Tuning-Free Algorithms, and Applications
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning: Modeling, Tuning-Free Algorithms, and Applications
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning : Modeling, Tuning-Free Algorithms, and Applications
Edité par
Springer International Publishing, 2023
ISBN 10 : 303122437X
ISBN 13 : 9783031224379
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent advances of Bayesian inference in structured tensor decompositions. It explains how Bayesian modeling and inference lead to tuning-free tensor decomposition algorithms, which achieve state-of-the-art performances in many applications, includingblind source separation;social network mining;image and video processing;array signal processing; and,wireless communications.The book begins with an introduction to the general topics of tensors and Bayesian theories. It then discusses probabilistic models of various structured tensor decompositions and their inference algorithms, with applications tailored for each tensor decomposition presented in the corresponding chapters. The book concludes by looking to the future, and areas where this research can be further developed.Bayesian Tensor Decomposition for Signal Processing and Machine Learning is suitable for postgraduates and researchers with interests in tensor data analytics and Bayesian methods. N° de réf. du vendeur 9783031224379
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning
Edité par
Springer International Publishing Feb 2023, 2023
ISBN 10 : 303122437X
ISBN 13 : 9783031224379
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents recent advances of Bayesian inference in structured tensor decompositions. It explains how Bayesian modeling and inference lead to tuning-free tensor decomposition algorithms, which achieve state-of-the-art performances in many applications, includingblind source separation;social network mining;image and video processing;array signal processing; and,wireless communications.The book begins with an introduction to the general topics of tensors and Bayesian theories. It then discusses probabilistic models of various structured tensor decompositions and their inference algorithms, with applications tailored for each tensor decomposition presented in the corresponding chapters. The book concludes by looking to the future, and areas where this research can be further developed.Bayesian Tensor Decomposition for Signal Processing and Machine Learning is suitable for postgraduates and researchers with interests in tensor data analytics and Bayesian methods. 196 pp. Englisch. N° de réf. du vendeur 9783031224379
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Bayesian Tensor Decomposition for Signal Processing and Machine Learning: Modeling, Tuning-Free Algorithms, and Applications
Vendeur : Books Puddle, New York, NY, Etats-Unis
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