Approximating functions in reproducing kernel Hilbert spaces via Statistical Learning Theory

Abstract: New non-asymptotic uniform error bounds for approximating func-tions in reproducing kernel Hilbert spaces are given using F. Girosi’s approach to derive approximation theoretic results from statistical learning theory. The authors congratulate Professor Charles Chui on the occasion of his sixty fifth birthday. 1