Sparse Polynomial Approximation of High-Dimensional Functions

Sparse Polynomial Approximation of High-Dimensional Functions presents a comprehensive and unified treatment of polynomial approximation techniques that are capable of mitigating the curse of dimensionality in high-dimensional approximation, including least squares and compressed sensing. The text develops main concepts in a mathematically rigorous manner, with full proofs given wherever possible, and it contains many numerical examples, each accompanied by downloadable code. The authors provide an extensive bibliography of over 350 relevant references, with an additional annotated bibliography available on the book’s companion website. This text is aimed at graduate students, postdoctoral fellows, and researchers in mathematics, computer science, and engineering who are interested in high-dimensional polynomial approximation techniques.

MATLAB and Parallel Computing Toolbox are used to solve application examples throughout the book.