Название: Tensor Decompositions for Data Science
Автор: Grey Ballard, Tamara G. Kolda
Издательство: Cambridge University Press
Год: 2025
Страниц: 423
Язык: английский
Формат: pdf (true)
Размер: 34.5 MB
Tensors are essential in modern day computational and Data Science. This book explores the foundations of tensor decompositions, a data analysis methodology that is ubiquitous in Machine Learning, signal processing, chemometrics, neuroscience, Quantum Computing, financial analysis, social science, business market analysis, image processing, and much more. In this self-contained mathematical, algorithmic, and computational treatment of tensor decomposition, the book emphasizes examples using real-world downloadable open-source datasets to ground the abstract concepts. Methodologies for 3-way tensors (the simplest notation) are presented before generalizing to d-way tensors (the most general but complex notation), making the book accessible to advanced undergraduate and graduate students in mathematics, Computer Science, statistics, engineering, and physical and life sciences. Additionally, extensive background materials in linear algebra, optimization, probability, and statistics are included as appendices. We do not prescribe a specific computational platform, but everything described here can be computed using the Tensor Toolbox for MATLAB. Much of the same functionality is available in its Python clone, the Python Tensor Toolbox (PyTTB).