Neural network approximation techniques have emerged as a formidable approach in computational mathematics and machine learning, providing robust tools for approximating complex functions. By ...

Low-rank approximation and dimensionality reduction techniques form the backbone of modern computational methods by enabling the efficient representation of large and high‐dimensional datasets. These ...

This work proposes a hyperspherical sparse approximation framework for detecting jump discontinuities in functions in high-dimensional spaces. The need for a novel approach results from the ...

A resource allocation algorithm proposed by Luss and Gupta is extended by the introduction of a numerical method for the optimal distribution of a continous resource among preselected activities as an ...