Semiparametric support vector and linear programming machines
1999
Conference Paper
ei
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 machines.
Author(s): | Smola, AJ. and Friess, T. and Schölkopf, B. |
Book Title: | Advances in Neural Information Processing Systems 11 |
Journal: | Advances in Neural Information Processing Systems |
Pages: | 585-591 |
Year: | 1999 |
Month: | June |
Day: | 0 |
Editors: | MS Kearns and SA Solla and DA Cohn |
Publisher: | MIT Press |
Department(s): | Empirical Inference |
Bibtex Type: | Conference Paper (inproceedings) |
Event Name: | Twelfth Annual Conference on Neural Information Processing Systems (NIPS 1998) |
Event Place: | Denver, CO, USA |
Address: | Cambridge, MA, USA |
Digital: | 0 |
Institution: | Royal Holloway College |
ISBN: | 0-262-11245-0 |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
PDF
Web |
BibTex @inproceedings{804, title = {Semiparametric support vector and linear programming machines}, author = {Smola, AJ. and Friess, T. and Sch{\"o}lkopf, B.}, journal = {Advances in Neural Information Processing Systems}, booktitle = {Advances in Neural Information Processing Systems 11}, pages = {585-591 }, editors = {MS Kearns and SA Solla and DA Cohn}, publisher = {MIT Press}, organization = {Max-Planck-Gesellschaft}, institution = {Royal Holloway College}, school = {Biologische Kybernetik}, address = {Cambridge, MA, USA}, month = jun, year = {1999}, doi = {}, month_numeric = {6} } |