Many applications of machine learning require development of sparse approximation and Banach space methods. Reproducing kernel Banach spaces provide a solid mathematical foundation for such purposes. We survey recent progress on the theory and construction of reproducing kernel Banach spaces. Applications of such spaces in sampling theory, machine learning and functional analysis will be introduced.

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