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Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data Hardcover – Dec 11 2013


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Product Details

  • Hardcover: 296 pages
  • Publisher: Chapman and Hall/CRC (Dec 11 2013)
  • Language: English
  • ISBN-10: 1439857245
  • ISBN-13: 978-1439857243
  • Product Dimensions: 15.7 x 2.3 x 23.6 cm
  • Shipping Weight: 558 g
  • Average Customer Review: Be the first to review this item
  • Amazon Bestsellers Rank: #2,144,874 in Books (See Top 100 in Books)
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Product Description

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

About the Author

Konstantinos Plataniotis is a Professor with the ECE Department at the University of Toronto (where he directs the Multimedia Laboratory), an adjunct Professor with the School of Computer Science at Ryerson University, Director of the Knowledge Media Design Institute, and Research Director of the Identity, Privacy and Security Institute at the University of Toronto. He has contributed chapters to fifteen books, co-authored the book Color Image Processing and Applications (2000), co-edited Color Imaging: Methods and Applications (2006) and published more than 350 technical papers.

Anastasios Venetsanopoulos is a Professor of Electrical and Computer Engineering at Ryerson University in Toronto, Ontario, and a Professor Emeritus with the Edward S. Rogers Department of Electrical and Computer Engineering at the University of Toronto. He has authored eight books, contributed chapters to thirty books and published over 830 technical papers. He is a Fellow of the Engineering Institute of Canada, the IEEE, the Canadian Academy of Engineering and the Royal Society of Canada.

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