Kernel methods in machine learning

First Page		Document Content
Date: 2008-07-14 12:36:36 Operator theory Hilbert space Linear algebra Signal processing Positive-definite kernel Reproducing kernel Hilbert space Kernel trick Fourier analysis Kernel principal component analysis Mathematics Mathematical analysis Algebra		Kernel methods in machine learning Add to Reading List Source URL: arxiv.org Download Document from Source Website File Size: 592,05 KB Share Document on Facebook

	The Journal of Fourier Analysis and Applications Moments of the Rudin-Shapiro Polynomials Christophe Doche, and Laurent Habsieger Communicated by Hans G. Feichtinger DocID: 1vewr - View Document
	IEEE TRANSACTIONS ON INFORMATION D. Slepian, “Prolate spheroidal wave functions, Fourier analysis and uncertainty-IV: Extension to many dimensions; Generalized prolate spheroidal functions,” Bell Syst. Tech. J., vol DocID: 1v1ML - View Document
	FOURIER ANALYSIS AND RELATED TOPICS BANACH CENTER PUBLICATIONS, VOLUME 56 INSTITUTE OF MATHEMATICS POLISH ACADEMY OF SCIENCES WARSZAWA 2002 DocID: 1uBqy - View Document
	Microsoft Word - Fourier analysis of the P53-MDM2 system - revised.doc DocID: 1ul1Q - View Document
	Uncertainty Principles for Fourier Multipliers Michael Northington, Georgia Institute of Technology Many questions in time-frequency analysis can be reduced to properties of a sequence of complex exponentials in certain DocID: 1u9xH - View Document