@inproceedings{796,
  title = {Incorporating invariances in support vector learning machines},
  journal = {Artificial Neural Networks --- ICANN‘96},
  booktitle = {Artificial Neural Networks: ICANN 96, LNCS vol. 1112},
  abstract = {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.},
  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
  },
  author = {Sch{\"o}lkopf, B. and Burges, C. and Vapnik, V.},
  doi = {10.1007/3-540-61510-5_12},
  month_numeric = {7}
}