Training invariant support vector machines

Decoste, D.; Scholkopf,  B.

dc.contributor.author	Decoste, D.	en_US
dc.contributor.author	Scholkopf, B.	en_US
dc.date.accessioned	2004-09-23T21:17:22Z
dc.date.available	2004-09-23T21:17:22Z
dc.date.issued	2002	en_US
dc.identifier.citation	Machine learning, 45, no. 1-3, pp. 161-190	en_US
dc.identifier.citation	Pasadena, CA USA	en_US
dc.identifier.clearanceno	00-1762	en_US
dc.identifier.uri	http://hdl.handle.net/2014/15949
dc.description.abstract	Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated into the training procedure.	en_US
dc.format.extent	624003 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en_US
dc.subject.other	Support vector machines invarianceimage classification	en_US
dc.title	Training invariant support vector machines	en_US