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Haasdonk, Bernard - Institut für Numerische und Angewandte Mathematik, Universität Münster
ALBERT-LUDWIGS-UNIVERSITAT FREIBURG INSTITUT FUR INFORMATIK
Learning with Distance Substitution Kernels Bernard Haasdonk 1 and Claus Bahlmann 2
Published in Proc. of the 16th Int. Conf. on Pattern Recognition (ICPR), Vol. 2, pp. 864--868, 2002. 864 Tangent Distance Kernels for Support Vector Machines
CONVERGENCE OF A STAGGERED LAX-FRIEDRICHS SCHEME FOR NONLINEAR CONSERVATION LAWS ON
Invariant Kernel Functions for Pattern Analysis and Machine Learning
Diplomarbeit Konvergenz eines
Mathematical Details Some mathematical expositions have been omitted main text improve readability. Here
Classification with Invariant Distance Substitution Kernels Bernard Haasdonk
Reduced Basis Method for Finite Volume Approximations of Parametrized Evolution Equations
CONVERGENCE OF A STAGGERED LAXFRIEDRICHS SCHEME FOR NONLINEAR CONSERVATION LAWS ON
h{p{MULTIRESOLUTION VISUALIZATION OF ADAPTIVE FINITE ELEMENT SIMULATIONS
Invariance Kernel Methods HaarIntegration Kernels
Digital Object Identifier (DOI) 10.1007/s002110000239 Numer. Math. (2001) 88: 459484
Classification with Invariant Distance Substitution Kernels
ALBERTLUDWIGSUNIVERSIT AT FREIBURG
Obje Ide ntifie (DOI) 10.1007/s002110000239 r. Math. (2001) 459--484
Multiresolution Visualization Higher Order Adaptive Finite Element Simulations
ALBERTLUDWIGSUNIVERSIT AT FREIBURG
Dissertation zur Erlangung des Doktorgrades
ALBERTLUDWIGSUNIVERSIT AT FREIBURG
USING TRANSFORMATION KNOWLEDGE FOR THE CLASSIFICATION OF RAMAN SPECTRA OF BIOLOGICAL SAMPLES
Invariant Kernel Functions for Pattern Analysis and Machine Learning
A Procedural Interface for Multiresolutional Visualization of General Numerical Data
Convergence of a staggered Lax-Friedrichs scheme on unstructured 2D-grids
Adjustable Invariant Features by Partial HaarIntegration Bernard Haasdonk, Alaa Halawani and Hans Burkhardt
Indefinite Kernel Fisher Discriminant Bernard Haasdonk Elzbieta Pekalska
Invariant Kernel Functions for Pattern Analysis and Machine Learning
Adaptive Basis Enrichment for the Reduced Basis Method Applied to
COPYRIGHT NOTICE 2005 IEEE. Personal material
Adaptive basis enrichment for the reduced basis method applied to finite volume schemes
2002 IEEE. Personal use material permitted. However, permission to reprint/
Adaptive basis enrichment for the reduced basis method applied to finite volume schemes
2002 IEEE. Personal use of this material is permitted. However, permission to reprint/ republish this material for advertising or promotional purposes or for creating new collective
Indefinite Kernel Fisher Discriminant Bernard Haasdonk Elzbieta Pekalska
A N G E W A N D T E M A T H E M A T I K I N F O R M A T I K
A N G E W A N D T E M A T H E M A T I K I N F O R M A T I K
Dissertation zur Erlangung des Doktorgrades
A Mathematical Details Some mathematical expositions have been omitted in the main text to improve readability. Here
ALBERT-LUDWIGS-UNIVERSIT AT FREIBURG INSTITUT F UR INFORMATIK
Multiresolution Visualization of Higher Order Adaptive Finite Element Simulations
Classification with Invariant Distance Substitution Kernels