Multilinear Subspace Learning by Haiping Lu - Bookswagon
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Home > Computing and Information Technology > Computer science > Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data(Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data(Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data(Chapman & Hall/CRC Machine Learning & Pattern Recognition)


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About the Book

Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniqu

Table of Contents:
Introduction. Fundamentals and Foundations: Linear Subspace Learning for Dimensionality Reduction. Fundamentals of Multilinear Subspace Learning. Overview of Multilinear Subspace Learning. Algorithmic and Computational Aspects. Algorithms and Applications: Multilinear Principal Component Analysis. Multilinear Discriminant Analysis. Multilinear ICA, CCA, and PLS. Applications of Multilinear Subspace Learning. Appendices. Bibliography. Index.

About the Author :
Haiping Lu, Konstantinos N. Plataniotis, Anastasios Venetsanopoulos

Review :
"…this book is built to be read as a rich and yet accessible introduction… artfully structured for a specialized audience of new researchers and bleeding-edge practitioners. …The treatment builds an overarching framework and provides an analytical reader with a well-expressed taxonomy on the foundations of historical developments and similarity in content and goals. Thus, packaged, current research is endowed with instant meaning and purpose, the derivation of which would initially elude a newcomer to this complex and articulated branch of machine learning." —Computing Reviews, November 2014 "Experimentally inclined readers will probably like this book … . Practitioners will appreciate that the presentation of the subject matter is goal oriented … The structure that this book builds can allow a neophyte to avoid much of the initial confusion and wasted effort necessary to classify unfamiliar work and distinguish between what may be useful or not to one’s intents and interests. … an exquisitely enriched literature review that is almost good enough to use as an auxiliary graduate textbook … a rich yet accessible introduction …" —Computing Reviews, October 2014


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Product Details
  • ISBN-13: 9781040197691
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman and Hall
  • Language: English
  • Sub Title: Dimensionality Reduction of Multidimensional Data
  • ISBN-10: 1040197698
  • Publisher Date: 11 Dec 2013
  • Binding: Digital (delivered electronically)
  • Series Title: Chapman & Hall/CRC Machine Learning & Pattern Recognition


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Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data(Chapman & Hall/CRC Machine Learning & Pattern Recognition)
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Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data(Chapman & Hall/CRC Machine Learning & Pattern Recognition)
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