Dimensionality Reduction
Miguel A. Carreira-Perpinan(Author)
Chapman & Hall/CRC (Publisher)
1st Edition
Published on 15. June 2015
Book
Hardback
320 pages
978-1-58488-653-2 (ISBN)
Description
Dimensionality reduction (DR) refers to the problem of projecting high-dimensional data onto a low-dimensional manifold so that relevant information is preserved. DR arises in many application areas where direct processing of the data is too costly. Through a machine-learning perspective that focuses on algorithms rather than theory, Dimensionality Reduction provides an overview of methods for DR including real-world applications taken from areas such as speech processing and computer vision. Interest in this area has exploded in recent years, making it a growing field of research. This book serves as the first reference for interested graduate students and researchers.
More details
Series
Language
English
Place of publication
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional
Product notice
Paper over boards
Illustrations
30 s/w Abbildungen
30 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
ISBN-13
978-1-58488-653-2 (9781584886532)
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Schweitzer Classification
Persons
Oregon Health & Science University, Beauerton, USA Rutgers University, New Brunswick, New Jersey, USA Carnegie Mellon University, Pennsylvania, USA Royal Holloway University of London, UK University of California, Irvine, California, USA
Author
Oregon Health & Science University, Beauerton, USA
Series Editor
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