Rakotomamonjy, Alain; Canu, Stéphane Frames, reproducing kernels, regularization and learning. (English) Zbl 1222.68284 J. Mach. Learn. Res. 6, 1485-1515 (2005). Summary: This work deals with a method for building a reproducing kernel Hilbert space (RKHS) from a Hilbert space with frame elements having special properties. Conditions on existence and a method of construction are given. Then, these RKHS are used within the framework of regularization theory for function approximation. Implications on semiparametric estimation are discussed and a multiscale scheme of regularization is also proposed. Results on toy and real-world approximation problems illustrate the effectiveness of such methods. Cited in 9 Documents MSC: 68T05 Learning and adaptive systems in artificial intelligence Keywords:regularization; kernel; frames; wavelets Software:TDSL PDFBibTeX XMLCite \textit{A. Rakotomamonjy} and \textit{S. Canu}, J. Mach. Learn. Res. 6, 1485--1515 (2005; Zbl 1222.68284) Full Text: Link