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Sparse Representation of Data and Support Vector Machines (in: Proceedings)

Georgiev, P. and Theis, Fabian J. and Ralescu, A. (2004) Sparse Representation of Data and Support Vector Machines (in: Proceedings). In: Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), 2004, Perugia, Italy.

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Abstract

We apply a new Blind Source Separation method (BSS), using sparseness, for identification of overdetermined linear mixing models, as we impose sparseness assumptions on the mixing matrix and no assumptions on the sources like independence or sparseness. We describe a suitable application of our method, for identification of kernel matrices in Support Vector Machines, under assumptions of ...

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Item Type:Conference or Workshop Item (UNSPECIFIED)
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang > Arbeitsgruppe Dr. Fabian Theis
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Subjects:500 Science > 530 Physics
500 Science > 570 Life sciences
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Owner: Redakteur Physik
Deposited On:20 Mar 2007
Last Modified:15 Oct 2010 06:35
Item ID:1612
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