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High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition

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Cover of 'High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition'

Table of Contents

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    Book Overview
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    Chapter 1 Adaptive Sparse Grid Model Order Reduction for Fast Bayesian Estimation and Inversion
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    Chapter 2 From Data to Uncertainty: An Efficient Integrated Data-Driven Sparse Grid Approach to Propagate Uncertainty
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    Chapter 3 Combination Technique Based Second Moment Analysis for Elliptic PDEs on Random Domains
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    Chapter 4 Adaptive Sparse Grids and Extrapolation Techniques
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    Chapter 5 A Cache-Optimal Alternative to the Unidirectional Hierarchization Algorithm
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    Chapter 6 Spatially-Dimension-Adaptive Sparse Grids for Online Learning
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    Chapter 7 Sparse Grids for the Vlasov–Poisson Equation
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    Chapter 8 An Adaptive Sparse Grid Algorithm for Elliptic PDEs with Lognormal Diffusion Coefficient
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    Chapter 9 A New Subspace-Based Algorithm for Efficient Spatially Adaptive Sparse Grid Regression, Classification and Multi-evaluation
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    Chapter 10 High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition
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    Chapter 11 Efficient Spectral-Element Methods for the Electronic Schrödinger Equation
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    Chapter 12 A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models
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    Chapter 13 Hierarchical Gradient-Based Optimization with B-Splines on Sparse Grids
Attention for Chapter 9: A New Subspace-Based Algorithm for Efficient Spatially Adaptive Sparse Grid Regression, Classification and Multi-evaluation
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Chapter title
A New Subspace-Based Algorithm for Efficient Spatially Adaptive Sparse Grid Regression, Classification and Multi-evaluation
Chapter number 9
Book title
Sparse Grids and Applications - Stuttgart 2014
Published by
Springer, Cham, January 2016
DOI 10.1007/978-3-319-28262-6_9
Book ISBNs
978-3-31-928260-2, 978-3-31-928262-6
Authors

David Pfander, Alexander Heinecke, Dirk Pflüger, Pfander, David, Heinecke, Alexander, Pflüger, Dirk

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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