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Incorporating invariances in support vector learning machines

1996

Conference Paper

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Developed only recently, support vector learning machines achieve high generalization ability by minimizing a bound on the expected test error; however, so far there existed no way of adding knowledge about invariances of a classification problem at hand. We present a method of incorporating prior knowledge about transformation invariances by applying transformations to support vectors, the training examples most critical for determining the classification boundary.

Author(s): Schölkopf, B. and Burges, C. and Vapnik, V.
Book Title: Artificial Neural Networks: ICANN 96, LNCS vol. 1112
Journal: Artificial Neural Networks --- ICANN‘96
Pages: 47-52
Year: 1996
Month: July
Day: 0
Editors: C von der Malsburg and W von Seelen and JC Vorbr{\"u}ggen and B Sendhoff
Publisher: Springer

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1007/3-540-61510-5_12
Event Name: 6th International Conference on Artificial Neural Networks
Event Place: Bochum, Germany

Address: Berlin, Germany
Digital: 0
ISBN: 3-540-61510-5
Note: volume 1112 of Lecture Notes in Computer Science
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF

BibTex

@inproceedings{796,
  title = {Incorporating invariances in support vector learning machines},
  author = {Sch{\"o}lkopf, B. and Burges, C. and Vapnik, V.},
  journal = {Artificial Neural Networks --- ICANN‘96},
  booktitle = {Artificial Neural Networks: ICANN 96, LNCS vol. 1112},
  pages = {47-52},
  editors = {C von der Malsburg and W von Seelen and JC Vorbr{\"u}ggen and B Sendhoff},
  publisher = {Springer},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Berlin, Germany},
  month = jul,
  year = {1996},
  note = {volume 1112 of Lecture Notes in Computer Science
  },
  month_numeric = {7}
}