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Multilinear Subspace Learning

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data

Written for students and researchers, Multilinear Subspace Learning gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. It covers the fundamentals, algorithms, and applications of MSL. Topics include tensor representation of multidimensional data, principal component analysis, and multilinear algebra preliminaries.

In addition, a supplemental set of MATLAB code files is available for download.

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About This Book

Haiping Lu, Hong Kong Baptist University
Konstantinos N. Plataniotis, University of Toronto
Anastasios Venetsanopoulos

CRC Press, Inc., 2014

ISBN: 978-1-4398-5724-3
Language: English