Matrix and Tensor Decomposition: Application to Data Fusion and Analysis

ISBN-13: 9780128157602 / Angielski / Miękka / 2024 / 400 str.

Institute for Information Christian Jutten (Deputy Director; Fr Grenoble GIPSA-Lab Dana Lahat (Postdoctoral Researcher; Department of Computer Science and E Tulay Adali (Professor

Opis

Matrix and Tensor Decomposition: Application to Data Fusion and Analysis introduces the main theoretical concepts for data fusion using matrix and tensor decompositions, beginning with the concept of "diversity", which facilitates identifiability. It provides the link between theoretical results and practice by addressing key implementation issues, such as model choice for a given problem, identification of sources of diversity, parameter selection and performance evaluation. Using rich diagrams to help communicate the main ideas and relationships among models and methods, this book presents a readily accessible reference for researchers on the methods and application of matrix and tensor decompositions.

Spis treści

1. Introduction 2. ICA and IVA: A Bottom-up Approach 3. ICA and IVA: A Top-down Approach 4. Sparse Decompositions 5. Nonnegative Decompositions 6. Tensor Decompositions 7. Data Fusion and Analysis Through 8. Data Fusion and Analysis Using General 9. Implementation Issues and Open