Abstract
AbstractMotivated by kernel methods in machine learning theory, we study the uniform approximation of functions from reproducing kernel Hilbert spaces by Bernstein operators. Rates of approximation are provided in terms of the function norm in the reproducing kernel Hilbert space. A case study of contracting properties of the Bernstein operators is also presented.
Funder
Research Grants Council of Hong Kong
Publisher
Springer Science and Business Media LLC
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