Learning multivariate functions with low-dimensional structures using polynomial bases
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Publication:2667104
DOI10.1016/j.cam.2021.113821zbMath1476.65024arXiv1912.03195OpenAlexW3202735065MaRDI QIDQ2667104
Publication date: 24 November 2021
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.03195
Multidimensional problems (41A63) Algorithms for approximation of functions (65D15) Approximate quadratures (41A55) Analysis of variance and covariance (ANOVA) (62J10)
Related Items (5)
ANOVAapprox ⋮ Grouped Transformations and Regularization in High-Dimensional Explainable ANOVA Approximation ⋮ Error guarantees for least squares approximation with noisy samples in domain adaptation ⋮ Learning in high-dimensional feature spaces using ANOVA-based fast matrix-vector multiplication ⋮ Interpretable Approximation of High-Dimensional Data
Uses Software
Cites Work
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- Breaking the curse of dimensionality in sparse polynomial approximation of parametric PDEs
- Quasi-Monte Carlo finite element methods for elliptic PDEs with lognormal random coefficients
- Application of quasi-Monte Carlo methods to elliptic PDEs with random diffusion coefficients: a survey of analysis and implementation
- Sparse grid quadrature in high dimensions with applications in finance and insurance
- Fast high-dimensional approximation with sparse occupancy trees
- Dimension-wise integration of high-dimensional functions with applications to finance
- The smoothing effect of the ANOVA decomposition
- Computing Fourier transforms and convolutions on the 2-sphere
- General foundations of high-dimensional model representations
- Circulant embedding with QMC: analysis for elliptic PDE with lognormal coefficients
- Numerical Fourier analysis
- Infinite-dimensional integration and the multivariate decomposition method
- The ANOVA decomposition of a non-smooth function of infinitely many variables can have every term smooth
- Multivariate Regression and Machine Learning with Sums of Separable Functions
- On decompositions of multivariate functions
- LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
- Fast algorithms for discrete polynomial transforms
- Quasi-Monte Carlo Finite Element Methods for a Class of Elliptic Partial Differential Equations with Random Coefficients
- Optimal Randomized Multilevel Algorithms for Infinite-Dimensional Integration on Function Spaces with ANOVA-Type Decomposition
- Sparse grids
- Estimating Mean Dimensionality of Analysis of Variance Decompositions
- Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
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