Open Problems in Spectral Dimensionality Reduction
The last few years have seen a great increase in the amount of data available to scientists. Datasets with millions of objects and hundreds, if not thousands of measurements are now commonplace in many disciplines. However, many of the computational techn
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Harry Strange Reyer Zwiggelaar
Open Problems in Spectral Dimensionality Reduction
SpringerBriefs in Computer Science
Series editors Stan Zdonik Peng Ning Shashi Shekhar Jonathan Katz Xindong Wu Lakhmi C. Jain David Padua Xuemin Shen Borko Furht V. S. Subrahmanian Martial Hebert Katsushi Ikeuchi Bruno Siciliano
For further volumes: http://www.springer.com/series/10028
Harry Strange Reyer Zwiggelaar •
Open Problems in Spectral Dimensionality Reduction
123
Reyer Zwiggelaar Department of Computer Science Aberystwyth University Aberystwyth UK
Harry Strange Department of Computer Science Aberystwyth University Aberystwyth UK
ISSN 2191-5768 ISBN 978-3-319-03942-8 DOI 10.1007/978-3-319-03943-5
ISSN 2191-5776 (electronic) ISBN 978-3-319-03943-5 (eBook)
Springer Cham Heidelberg New York Dordrecht London Library of Congress Control Number: 2013956626 The Author(s) 2014 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
The ability to simplify means to eliminate the unnecessary so that the necessary may speak. —Hans Hofmann, 1880–1966
The last few years have seen a great increase in the amount of data available to scientists, engineers, and researchers from many disciplines. Datasets with millions of objects and hundreds, if not thousands, of measureme
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