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    » On the Noise Model of Support Vector Machines Regression
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    ESANN
    2007
    112views Neural Networks» more  ESANN 2007»
    Model Selection for Kernel Probit Regression
    13 years 10 months ago
    Model Selection for Kernel Probit Regression
    Download  www.dice.ucl.ac.be
    Abstract. The convex optimisation problem involved in fitting a kernel probit regression (KPR) model can be solved efficiently via an iteratively re-weighted least-squares (IRWLS)...
    Gavin C. Cawley
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    MCS
    2002
    Springer
    146views Pattern Recognition» more  MCS 2002»
    Support Vector Machines, Kernel Logistic Regression and Boosting
    13 years 8 months ago
    Support Vector Machines, Kernel Logistic Regression and Boosting
    Download  www-stat.stanford.edu
    Ji Zhu, Trevor Hastie
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    NIPS
    1996
    87views Information Technology» more  NIPS 1996»
    Support Vector Regression Machines
    13 years 10 months ago
    Support Vector Regression Machines
    Download  reference.kfupm.edu.sa
    Harris Drucker, Christopher J. C. Burges, Linda Ka...
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    JMLR
    2008
    81views more  JMLR 2008»
    Bouligand Derivatives and Robustness of Support Vector Machines for Regression
    13 years 8 months ago
    Bouligand Derivatives and Robustness of Support Vector Machines for Regression
    Download  homepages.vub.ac.be
    Andreas Christmann, Arnout Van Messem
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    PAKDD
    2007
    ACM
    128views Data Mining» more  PAKDD 2007»
    Selecting a Reduced Set for Building Sparse Support Vector Regression in the Primal
    14 years 2 months ago
    Selecting a Reduced Set for Building Sparse Support Vector Regression in the Primal
    Download  ttic.uchicago.edu
    Recent work shows that Support vector machines (SVMs) can be solved efficiently in the primal. This paper follows this line of research and shows how to build sparse support vector...
    Liefeng Bo, Ling Wang, Licheng Jiao
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