Open Problems in Spectral Dimensionality Reduction
SpringerBriefs in Computer Science
1st Edition
Published on 7. January 2014
IX, 92 pages
978-3-319-03943-5 (ISBN)
Description
The last few years have seen a great increase in the amount of data available to scientists, yet many of the techniques used to analyse this data cannot cope with such large datasets. Therefore, strategies need to be employed as a pre-processing step to reduce the number of objects or measurements whilst retaining important information. Spectral dimensionality reduction is one such tool for the data processing pipeline. Numerous algorithms and improvements have been proposed for the purpose of performing spectral dimensionality reduction, yet there is still no gold standard technique. This book provides a survey and reference aimed at advanced undergraduate and postgraduate students as well as researchers, scientists, and engineers in a wide range of disciplines. Dimensionality reduction has proven useful in a wide range of problem domains and so this book will be applicable to anyone with a solid grounding in statistics and computer science seeking to apply spectral dimensionality to their work.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
IX, 92 p. 20 illus., 15 illus. in color.
File size
3,53 MB
ISBN-13
978-3-319-03943-5 (9783319039435)
DOI
10.1007/978-3-319-03943-5
Schweitzer Classification
Other editions
Additional editions
Harry Strange | Reyer Zwiggelaar
Open Problems in Spectral Dimensionality Reduction
Book
01/2014
Springer
€53.49
Shipment within 10-15 days
Content
Introduction.- Spectral Dimensionality Reduction.- Modelling the Manifold.- Intrinsic Dimensionality.- Incorporating New Points.- Large Scale Data.- Postcript.
