Topological and Statistical Methods for Complex Data

Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces

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Last edited by MARC Bot
August 12, 2024 | History

Topological and Statistical Methods for Complex Data

Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces

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.

Publish Date
Publisher
Springer
Pages
297

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Book Details


Edition Notes

Source title: Topological and Statistical Methods for Complex Data: Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces (Mathematics and Visualization)

Classifications

Library of Congress
QA1-939, QA611-614.97

The Physical Object

Format
hardcover
Number of pages
297

Edition Identifiers

Open Library
OL29327806M
ISBN 10
3662448998
ISBN 13
9783662448991

Work Identifiers

Work ID
OL20676718W

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August 12, 2024 Edited by MARC Bot import existing book
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August 24, 2020 Created by ImportBot Imported from amazon.com record