Overview
- Latest peer-reviewed results in a growing research area
- Many applications in science and engineering
- Important contributions to the fields of mathematics and computer science?
- Includes supplementary material: sn.pub/extras
Part of the book series: Mathematics and Visualization (MATHVISUAL)
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Table of contents (16 papers)
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Front Matter
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Large-Scale Data Analysis: In-Situ and Distributed Analysis
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Front Matter
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Large-Scale Data Analysis: Efficient Representation of Large Functions
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Front Matter
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Multi-Variate Data Analysis: Structural Techniques
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Front Matter
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Multi-Variate Data Analysis: Classification and Visualization of Vector Fields
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Front Matter
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High-Dimensional Data Analysis: Exploration of High-Dimensional Models
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Front Matter
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Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Topological and Statistical Methods for Complex Data
Book Subtitle: Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces
Editors: Janine Bennett, Fabien Vivodtzev, Valerio Pascucci
Series Title: Mathematics and Visualization
DOI: https://doi.org/10.1007/978-3-662-44900-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-44899-1Published: 03 December 2014
Softcover ISBN: 978-3-662-51370-5Published: 20 August 2016
eBook ISBN: 978-3-662-44900-4Published: 19 November 2014
Series ISSN: 1612-3786
Series E-ISSN: 2197-666X
Edition Number: 1
Number of Pages: XV, 297
Number of Illustrations: 19 b/w illustrations, 101 illustrations in colour
Topics: Topology, Statistical Theory and Methods, Applications of Mathematics, Algorithms, Visualization, Manifolds and Cell Complexes (incl. Diff.Topology)