NeurIPS Conference 1998 Conference Paper
Semiparametric Support Vector and Linear Programming Machines
- Alex Smola
- Thilo-Thomas Frieß
- Bernhard Schölkopf
Semiparametric models are useful tools in the case where domain knowledge exists about the function to be estimated or emphasis is put onto understandability of the model. We extend two learning algorithms - Support Vector machines and Linear Programming machines to this case and give experimental results for SV ma(cid: 173) chines.