Prior knowledge in support vector kernels

Schölkopf, B; Simard, P; Smola, AJ; Vapnik, V

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Prior knowledge in support vector kernels

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Schölkopf, B
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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http://papers.nips.cc/paper/1457-prior-knowledge-in-support-vector-kernels.pdf
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Citation

Schölkopf, B., Simard, P., Smola, A., & Vapnik, V. (1998). Prior knowledge in support vector kernels. In M. Jordan, M. Kearns, & S. Solla (Eds.), Advances in Neural Information Processing Systems 10 (pp. 640-646). Cambridge, MA, USA: MIT Press.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-E871-3

Abstract

We explore methods for incorporating prior knowledge about a problem at hand in Support Vector learning machines. We show that both invari-ances under group transfonnations and prior knowledge about locality in images can be incorporated by constructing appropriate kernel functions.