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 |