Nonnegative Matrix and Tensor Factorizations (Repost)

This book provides a broad survey of models and efficientalgorithms for Nonnegative Matrix Factorization (NMF). Thisincludes NMF’s various extensions and modifications,especially Nonnegative Tensor Factorizations (NTF) and NonnegativeTucker Decompositions (NTD). NMF/NTF and their extensions areincreasingly used as tools in signal and image processing, and dataanalysis, having garnered interest due to their capability toprovide new insights and relevant information about the complexlatent relationships in experimental data sets. It is suggestedthat NMF can provide meaningful components with physicalinterpretations; for example, in bioinformatics, NMF and itsextensions have been successfully applied to gene expression,sequence analysis, the functional characterization of genes,clustering and text mining. As such, the authors focus on thealgorithms that are most useful in practice, looking at thefastest, most robust, and suitable for large-scale models.
Key features:
- Acts as a single source reference guide to NMF, collatinginformation that is widely dispersed in current literature,including the authors’ own recently developed techniques inthe subject area.
- Uses generalized cost functions such as Bregman, Alpha and Betadivergences, to present practical implementations of several typesof robust algorithms, in particular Multiplicative, AlternatingLeast Squares, Projected Gradient and Quasi Newton algorithms.
- Provides a comparative analysis of the different methods inorder to identify approximation error and complexity.
- Includes pseudo codes and optimized MATLAB source codes foralmost all algorithms presented in the book.
The increasing interest in nonnegative matrix and tensorfactorizations, as well as decompositions and sparse representationof data, will ensure that this book is essential reading forengineers, scientists, researchers, industry practitioners andgraduate students across signal and image processing; neuroscience;data mining and data analysis; computer science; bioinformatics;speech processing; biomedical engineering; and multimedia.