Topological and Statistical Methods for Complex Data Tackling Large-Scale, High-Dimensional, and Multivariate Data Spaces

✍ Scribed by Bennett, Janine;Pascucci, Valerio;Vivodtzev, Fabien

• Publisher: Springer
• Year: 2015
• Tongue: English
• Leaves: 297
• Series: Mathematics and Visualization
• Edition: 1st ed.
• Category: Library

✦ Table of Contents

Part I. Large-Scale Data Analysis: In-Situ and Distributed Analysis: 1 A Distributed-Memory Algorithm for Connected Components Labeling of Simulation Data: Cyrus Harrison, Jordan Weiler, Ryan Bleile, Kelly Gaither and Hank Childs.- 2 In-Situ Visualization in Fluid Mechanics Using Open-Source Tools: Integration of Catalyst into Code Saturne: Alejandro Ribes, Benjamin Lorendeau, Julien Jomier and Yvan Fournier.- 3 Sublinear Algorithms for Extreme-Scale Data Analysis: C. Seshadhri, Ali Pinar, David Thompson and Janine Bennett.- Part II. Large-Scale Data Analysis: Efficient Representation of Large-Functions: 4 Optimal General Simplification of Scalar Fields on Surfaces: Julien Tierny, David Guenther and Valerio Pascucci.- 5 Piecewise Polynomial Monotonic Interpolation of 2D Gridded Data: Leo Allemand-Giorgis, Georges-Pierre Bonneau, Stefanie Hahmann and Fabien Vivodtzev.- 6 Shape Analysis and Description Using Real Functions: Silvia Biasotti, Andrea Cerri, Michela Spagnuolo and Bianca Falcidieno.- Part III. Multi-Variate Data Analysis: Structural Techniques: 7 3D Symmetric Tensor Fields: What We Know and Where To Go Next: Eugene Zhang and Yue Zhang.- 8 A Comparison of Pareto Sets and Jacobi Sets: Lars Huettenberger and Christoph Garth.- 9 Deformations Preserving Gauss Curvature: Anne Berres, Hans Hagen and Stefanie Hahmann.- Part IV. Multi-Variate Data Analysis: Classification and Visualization of Vector Fields: 10 Lyapunov Time for 2D Lagrangian Visualization: Filip Sadlo.- 11 Geometric Algebra for Vector Fields Analysis and Visualization: Mathematical Settings, Overview and Applications: Chantal Oberson Ausoni and Pascal Frey.- 12 Computing Accurate Morse-Smale Complexes from Gradient Vector Fields: Attila Gyulassy, Harsh Bhatia, Peer-Timo Bremer and Valerio Pascucci.- Part V. High-Dimensional Data Analysis: Exploration of High-Dimensional Models: 13 Exercises in High-Dimensional Sampling: Maximal Poisson-Disk Sampling and k-d Darts: Mohamed S. Ebeida, Scott A. Mitchell, Anjul Patney, Andrew A. Davidson, Stanley Tzeng, Muhammad A. Awad, Ahmed H. Mahmoud, and John D. Owens.- 14 Realization of Regular Maps of Large Genus: Faniry Razafindrazaka and Konrad Polthier.- Part VI. High-Dimensional Data Analysis: Analysis of Large Systems: 15 Polynomial-Time Amoeba Neighborhood Membership and Faster Localized Solving: Eleanor Anthony, Sheridan Grant, Peter Gritzmann, and J. Maurice Rojas.- 16 Slycat Ensemble Analysis of Electrical Circuit Simulations: Patricia J. Crossno, Timothy M. Shead, Milosz A. Sielicki, Warren L. Hunt, Shawn Martin, and Ming-Yu Hsieh.

✦ Subjects

(BIC Subject Heading)PBP;(BISAC Subject Heading)MAT038000;Data Analysis;High-Dimensional Data;Large-Scale Data;(Produktform)Paperback / softback;(Springer Marketing Classification)C;(Springer Subject Code)SCM13003: Applications of Mathematics;(Springer Subject Code)SCM14018: Algorithms;(Springer Subject Code)SCM14034: Visualization;(Springer Subject Code)SCM28000: Topology;(Springer Subject Code)SCM28027: Manifolds and Cell Complexes (incl. Diff. Topology);(Springer Subject Code)SCS11001: Statis