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portada Bayesian Tensor Decomposition for Signal Processing and Machine Learning
Type
Physical Book
Publisher
Author
Year
2023
Language
English
Pages
196
Format
Paperback
Dimensions
23.4x15.6 cm
ISBN13
9783031224393

Bayesian Tensor Decomposition for Signal Processing and Machine Learning

Lei Cheng;Yik-Chung Wu;Zhongtao Chen (Author) · Springer Nature B.V. · Paperback

Bayesian Tensor Decomposition for Signal Processing and Machine Learning - Lei Cheng;Yik-Chung Wu;Zhongtao Chen

New Book Imported to Taiwan
Delivery: 10 Sep - 18 Sep Shipping: 5 to 6 business days.
NT$ 2,159
NT$ 2,159

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Synopsis "Bayesian Tensor Decomposition for Signal Processing and Machine Learning"

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.

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