E-Book Overview
This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013. It features the work of some of the most prominent and recognized leaders in the field who examine challenges as well as detail solutions to the analysis of extreme scale data.
The book presents new methods that leverage the mutual strengths of both topological and statistical techniques to support the management, analysis, and visualization of complex data. It covers both theory and application and provides readers with an overview of important key concepts and the latest research trends.
Coverage in the book includes multi-variate and/or high-dimensional analysis techniques, feature-based statistical methods, combinatorial algorithms, scalable statistics algorithms, scalar and vector field topology, and multi-scale representations. In addition, the book details algorithms that are broadly applicable and can be used by application scientists to glean insight from a wide range of complex data sets.
E-Book Content
Mathematics and Visualization Janine Bennett · Fabien Vivodtzev Valerio Pascucci╇ Editors Topological and Statistical Methods for Complex Data Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces Mathematics and Visualization Series Editors Gerald Farin Hans-Christian Hege David Hoffman Christopher R. Johnson Konrad Polthier Martin Rumpf More information about this series at http://www.springer.com/series/4562 Janine Bennett Fabien Vivodtzev Valerio Pascucci Editors Topological and Statistical Methods for Complex Data Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces With 120 Figures, 101 in color 123 Editors Janine Bennett Sandia National Laboratories Livermore, CA USA Fabien Vivodtzev CEA CESTA, CS 60001 Le Barp CEDEX France Valerio Pascucci School of Computing and SCI Institute University of Utah Salt Lake City, UT USA ISSN 1612-3786 ISSN 2197-666X (electronic) ISBN 978-3-662-44899-1 ISBN 978-3-662-44900-4 (eBook) DOI 10.1007/978-3-662-44900-4 Springer Heidelberg New York Dordrecht London Library of Congress Control Number: 2014955717 Mathematics Subject Classification (2010): 54-02, 62-02, 62-07 c Springer-Verlag Berlin Heidelberg 2015 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