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  Incorporating invariances in support vector learning machines

Schölkopf, B., Burges, C., & Vapnik, V. (1996). Incorporating invariances in support vector learning machines. In C. von der Malsburg, W. von Seelen, J. Vorbrüggen, & B. Sendhoff (Eds.), Artificial Neural Networks: ICANN 96: 1996 International Conference Bochum, Germany, July 16–19, 1996 (pp. 47-52). Berlin, Germany: Springer.

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 Creators:
Schölkopf, B1, 2, Author           
Burges, C, Author
Vapnik, V, Author           
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497797              

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 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.

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 Dates: 1996-07
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.1007/3-540-61510-5_12
BibTex Citekey: 796
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Title: 6th International Conference on Artificial Neural Networks (ICANN 1996)
Place of Event: Bochum, Germany
Start-/End Date: 1996-07-16 - 1996-07-19

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Title: Artificial Neural Networks: ICANN 96: 1996 International Conference Bochum, Germany, July 16–19, 1996
Source Genre: Proceedings
 Creator(s):
von der Malsburg, C, Editor
von Seelen, W, Editor
Vorbrüggen, JC, Editor
Sendhoff, B, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 47 - 52 Identifier: ISBN: 3-540-61510-5

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 1112 Sequence Number: - Start / End Page: - Identifier: -