
Title:
Bayesian Tensor Decomposition for Signal Processing and Machine Learning Modeling, Tuning-Free Algorithms, and Applications
Author:
Cheng, Lei. author.
ISBN:
9783031224386
Edition:
1st ed. 2023.
Physical Description:
X, 183 p. 61 illus., 41 illus. in color. online resource.
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.
Added Corporate Author:
Electronic Access:
https://doi.org/10.1007/978-3-031-22438-6Copies: 1