Emphasizing essential concepts and system-level perspectives, this book provides a foundation for solving many of today's most interesting and challenging problems in big multidimensional data processing. It gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. The book follows a unifying MSL framework formulation to systematically derive representative MSL algorithms. It describes various applications of the algorithms ...
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Emphasizing essential concepts and system-level perspectives, this book provides a foundation for solving many of today's most interesting and challenging problems in big multidimensional data processing. It gives a comprehensive introduction to both theoretical and practical aspects of MSL for the dimensionality reduction of multidimensional data based on tensors. The book follows a unifying MSL framework formulation to systematically derive representative MSL algorithms. It describes various applications of the algorithms, along with their pseudocode. Supporting materials are available online.
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Add this copy of Multilinear Subspace Learning: Dimensionality Reduction to cart. $207.00, good condition, Sold by Bonita rated 4.0 out of 5 stars, ships from Santa Clarita, CA, UNITED STATES, published 2013 by Chapman and Hall/CRC.
