Learning multivariate functions with low-dimensional structures using polynomial bases
نویسندگان
چکیده
In this paper we propose a method for the approximation of high-dimensional functions over finite intervals with respect to complete orthonormal systems polynomials. An important tool is multivariate classical analysis variance (ANOVA) decomposition. For low-dimensional structure, i.e., low superposition dimension, are able achieve reconstruction from scattered data and simultaneously understand relationships between different variables.
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ژورنال
عنوان ژورنال: Journal of Computational and Applied Mathematics
سال: 2022
ISSN: ['0377-0427', '1879-1778', '0771-050X']
DOI: https://doi.org/10.1016/j.cam.2021.113821