Efficient High-Dimensional Approximation: ANOVA Decomposition Meets Wavelets and Random Fourier Features
Laura Weidensager
Broschiertes Buch

Efficient High-Dimensional Approximation: ANOVA Decomposition Meets Wavelets and Random Fourier Features

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In this thesis, we focus on the problem of reconstructing a multivariate function from discrete d-dimensional samples. Beyond achieving accurate function recovery, we aim to enhance interpretability by identifying how individual variables and their interactions influence the target function. To this end, we develop several efficient hybrid methods that combine the ANOVA decomposition, wavelet techniques, and random Fourier features. The multi-resolution capabilities of wavelets and the scalability of random Fourier features, paired with the interpretability provided by the ANOVA decomposition,...