Greedy Kernel Approximation for Sparse Surrogate Modeling

DOI10.1007/978-3-319-75319-5_2zbMath1416.65059OpenAlexW2796773687MaRDI QIDQ5225296

Bernard Haasdonk, Gabriele Santin

Publication date: 19 July 2019

Published in: Reduced-Order Modeling (ROM) for Simulation and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-75319-5_2

Mathematics Subject Classification ID

Numerical interpolation (65D05) Algorithms for approximation of functions (65D15)

Related Items (8)

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario ⋮ Analysis of target data-dependent greedy kernel algorithms: convergence rates for \(f\)-, \(f \cdot P\)- and \(f/P\)-greedy ⋮ An adaptive sparse kernel technique in greedy algorithm framework to simulate an anomalous solute transport model ⋮ A novel class of stabilized greedy kernel approximation algorithms: convergence, stability and uniform point distribution ⋮ Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods ⋮ 9 Kernel methods for surrogate modeling ⋮ Stable interpolation with exponential-polynomial splines and node selection via greedy algorithms ⋮ Adaptive Interpolatory MOR by Learning the Error Estimator in the Parameter Domain

Uses Software

• Matlab
• LIBSVM
• rbf_qr

Cites Work

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• Multivariate interpolation with increasingly flat radial basis functions of finite smoothness
• Bases for kernel-based spaces
• A Newton basis for kernel spaces
• Some observations regarding interpolants in the limit of flat radial basis functions
• Near-optimal data-independent point locations for radial basis function interpolation
• Error estimates and condition numbers for radial basis function interpolation
• Theoretical and computational aspects of multivariate interpolation with increasingly flat radial basis functions
• Stable Evaluation of Gaussian Radial Basis Function Interpolants
• Surrogate modeling of multiscale models using kernel methods
• Stable Computations with Gaussian Radial Basis Functions
• Support Vector Machines
• A note on radial basis function interpolant limits
• Greedy approximation
• Convergence rate of the data-independent $P$-greedy algorithm in kernel-based approximation
• Approximation of Large-Scale Dynamical Systems
• Scattered Data Approximation

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