MDL Based Model Selection for Relevance Vector Regression by Davide Anguita, Matteo Gagliolo, José Dorronsoro Computer and Information Science › Miscellaneous Papers View in Mendeley DesktopIn your librarySave PDF to library Share Short URL Share on Facebook Share on Twitter Overview Related research Artificial Neural Networks ICANN 2002 (2002) Publisher: Springer, Pages: 468-473 DOI: 10.1007/3-540-46084-5_76 Available from www.springerlink.com or Find this paper at: openurl.ac.uk WorldCat® Google Scholar Edit library access links Related research Sparse support vector regression based on orthogonal forward selection for the generalised kernel model X X Wang, S Chen, D Lowe, C J Harris in Neurocomputing (2006) Efficient parameter selection for support vector machines in classification and regression via model-based global optimization H Frohlich, A Zell in 4th Kuala Lumpur International Conference on Biomedical Engineering (2008) Least Square-Support Vector Regression based Car-following Model with Sparse Sample Selection Dali Wei, Feng Chen, Tongshuang Zhang in Science And Technology (2010) Time Series Regression Based on Relevance Vector Learning Mechanism Huazhu Song in Science And Technology (2008) Application of relevance vector regression model based on sparse bayesian learning to long-term electricity demand forecasting Lin Niu, Jianguo Zhao, Min Liu in 2009 International Conference on Mechatronics and Automation (2009) More related papers Cite this document (BETA) APABibTeXCellChicagoHarvardMLANatureScience APA BibTeX Cell Chicago Harvard MLA Nature Science Choose a citation style from the tabs above. Click to zoom in 7 pages available to preview Close Available from www.springerlink.com Page 1 MDL Based Model Selection for Relevance Vector Regression
Sparse support vector regression based on orthogonal forward selection for the generalised kernel model X X Wang, S Chen, D Lowe, C J Harris in Neurocomputing (2006)
Efficient parameter selection for support vector machines in classification and regression via model-based global optimization H Frohlich, A Zell in 4th Kuala Lumpur International Conference on Biomedical Engineering (2008)
Least Square-Support Vector Regression based Car-following Model with Sparse Sample Selection Dali Wei, Feng Chen, Tongshuang Zhang in Science And Technology (2010)
Time Series Regression Based on Relevance Vector Learning Mechanism Huazhu Song in Science And Technology (2008)
Application of relevance vector regression model based on sparse bayesian learning to long-term electricity demand forecasting Lin Niu, Jianguo Zhao, Min Liu in 2009 International Conference on Mechatronics and Automation (2009)