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Topological and statistical methods ...

Bennett, Janine.

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Topological and statistical methods for complex data = tackling large-scale, high-dimensional, and multivariate data spaces /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Topological and statistical methods for complex data/ edited by Janine Bennett, Fabien Vivodtzev, Valerio Pascucci.
Reminder of title:	tackling large-scale, high-dimensional, and multivariate data spaces /
other author:	Bennett, Janine.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xv, 297 p. :ill., digital ;24 cm.
[NT 15003449]:	I. Large-scale data analysis: In-situ and distributed analysis -- II. Large-scale data analysis: Efficient representation of large-functions -- III. Multi-variate data analysis: Structural techniques -- IV. Multi-variate data analysis: Classification and visualization of vector fields -- V. High-dimensional data analysis: Exploration of high-dimensional models -- VI. High-dimensional data analysis: Analysis of large systems.
Contained By:	Springer eBooks
Subject:	Topology. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-44900-4
ISBN:	9783662449004 (electronic bk.)

Topological and statistical methods for complex data = tackling large-scale, high-dimensional, and multivariate data spaces /
Topological and statistical methods for complex datatackling large-scale, high-dimensional, and multivariate data spaces /[electronic resource] :edited by Janine Bennett, Fabien Vivodtzev, Valerio Pascucci. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xv, 297 p. :ill., digital ;24 cm. - Mathematics and visualization,1612-3786. - Mathematics and visualization..

I. Large-scale data analysis: In-situ and distributed analysis -- II. Large-scale data analysis: Efficient representation of large-functions -- III. Multi-variate data analysis: Structural techniques -- IV. Multi-variate data analysis: Classification and visualization of vector fields -- V. High-dimensional data analysis: Exploration of high-dimensional models -- VI. High-dimensional data analysis: Analysis of large systems.

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.

ISBN: 9783662449004 (electronic bk.)

Standard No.: 10.1007/978-3-662-44900-4doiSubjects--Topical Terms:

522026
Topology.

LC Class. No.: QA611

Dewey Class. No.: 514

Topological and statistical methods for complex data = tackling large-scale, high-dimensional, and multivariate data spaces /
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245 0 0 $a Topological and statistical methods for complex data $h [electronic resource] : $b tackling large-scale, high-dimensional, and multivariate data spaces / $c edited by Janine Bennett, Fabien Vivodtzev, Valerio Pascucci.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2015.
300 $a xv, 297 p. : $b ill., digital ; $c 24 cm.
490 1 $a Mathematics and visualization, $x 1612-3786
505 0 $a I. Large-scale data analysis: In-situ and distributed analysis -- II. Large-scale data analysis: Efficient representation of large-functions -- III. Multi-variate data analysis: Structural techniques -- IV. Multi-variate data analysis: Classification and visualization of vector fields -- V. High-dimensional data analysis: Exploration of high-dimensional models -- VI. High-dimensional data analysis: Analysis of large systems.
520 $a 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.
650 0 $a Topology. $3 522026
650 0 $a Mathematical analysis. $3 516833
650 0 $a Visualization. $3 586179
650 1 4 $a Mathematics. $3 515831
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Applications of Mathematics. $3 890893
650 2 4 $a Algorithms. $3 536374
650 2 4 $a Manifolds and Cell Complexes (incl. Diff.Topology) $3 891270
700 1 $a Bennett, Janine. $3 2132171
700 1 $a Vivodtzev, Fabien. $3 2132172
700 1 $a Pascucci, Valerio. $3 1531477
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Mathematics and visualization. $3 1568010
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-44900-4
950 $a Mathematics and Statistics (Springer-11649)