Bayesian Tensor Decomposition for Signal Processing and Machine Learning: Modeling, Tuning-Free Algorithms, and Applications

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. ...