Bayesian Tensor Decomposition for Signal Processing and Machine Learning
Modeling, Tuning-Free Algorithms, and Applications
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Product details:
- Edition number 1st ed. 2023
- Publisher Springer International Publishing
- Date of Publication 17 February 2024
- Number of Volumes 1 pieces, Book
- ISBN 9783031224409
- Binding Paperback
- See also 9783031224379
- No. of pages183 pages
- Size 235x155 mm
- Weight 344 g
- Language English
- Illustrations X, 183 p. 61 illus., 41 illus. in color. Illustrations, black & white 538
Categories
Long description:
- blind source separation;
- social network mining;
- image and video processing;
- array signal processing; and,
- wireless communications.
Table of Contents:
Tensor decomposition: Basics, algorithms, and recent advances.- Bayesian learning for sparsity-aware modeling.- Bayesian tensor CPD: Modeling and inference.- Bayesian tensor CPD: Performance and real-world applications.- When stochastic optimization meets VI: Scaling Bayesian CPD to massive data.- Bayesian tensor CPD with nonnegative factors.- Complex-valued CPD, orthogonality constraint and beyond Gaussian noises.- Handling missing value: A case study in direction-of-arrival estimation.- From CPD to other tensor decompositions.
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