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.

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

Inhalt

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.