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Incorporating Invariances in Non-Linear Support Vector Machines

2001

Technical Report

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We consider the problem of how to incorporate in the Support Vector Machine (SVM) framework invariances given by some a priori known transformations under which the data should be invariant. It extends some previous work which was only applicable with linear SVMs and we show on a digit recognition task that the proposed approach is superior to the traditional Virtual Support Vector method.

Author(s): Chapelle, O. and Schölkopf, B.
Year: 2001
Day: 0

Department(s): Empirical Inference
Bibtex Type: Technical Report (techreport)

Institution: Max Planck Institute for Biological Cybernetics / Biowulf Technologies

Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PostScript

BibTex

@techreport{2166,
  title = {Incorporating Invariances in Non-Linear Support Vector Machines},
  author = {Chapelle, O. and Sch{\"o}lkopf, B.},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics / Biowulf Technologies},
  school = {Biologische Kybernetik},
  year = {2001}
}