Summary: ALBERT-LUDWIGS-UNIVERSIT¨AT FREIBURG
INSTITUT F¨UR INFORMATIK
Lehrstuhl f¨ur Mustererkennung und Bildverarbeitung
Learning Equivariant Functions with Matrix
Valued Kernels - Theory and Applications
Internal Report 1/06
Marco Reisert
June 2006
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Learning Equivariant Functions with Matrix Valued
Kernels - Theory and Applications
Marco Reisert
Computer Science Department
Albert-Ludwigs-University Freiburg
79110 Freiburg, Germany
reisert@informatik.uni-freiburg.de
March, 2005
Abstract
This paper presents a new class of matrix valued kernels, which are ideally
suited to learn vector valued equivariant functions. Matrix valued kernels are a

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

Collections: Computer Technologies and Information Sciences