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    » Training of Support Vector Machines with Mahalanobis Kernels
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    IJDMB
    2006
    96views more  IJDMB 2006»
    Kernel design for RNA classification using Support Vector Machines
    14 years 9 months ago
    Kernel design for RNA classification using Support Vector Machines
    Download  web.njit.edu
    Jason T. L. Wang, Xiaoming Wu
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    MCS
    2002
    Springer
    146views Pattern Recognition» more  MCS 2002»
    Support Vector Machines, Kernel Logistic Regression and Boosting
    14 years 9 months ago
    Support Vector Machines, Kernel Logistic Regression and Boosting
    Download  www-stat.stanford.edu
    Ji Zhu, Trevor Hastie
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    ICANN
    2001
    Springer
    172views Neural Networks» more  ICANN 2001»
    The Bayesian Committee Support Vector Machine
    15 years 2 months ago
    The Bayesian Committee Support Vector Machine
    Download  wwwbrauer.in.tum.de
    Empirical evidence indicates that the training time for the support vector machine (SVM) scales to the square of the number of training data points. In this paper, we introduce the...
    Anton Schwaighofer, Volker Tresp
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    ICANN
    2007
    Springer
    129views Neural Networks» more  ICANN 2007»
    Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
    15 years 3 months ago
    Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
    Download  www.lib.kobe-u.ac.jp
    Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
    Shigeo Abe, Kenta Onishi
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    ICML
    2005
    IEEE
    130views Machine Learning» more  ICML 2005»
    Core Vector Regression for very large regression problems
    15 years 10 months ago
    Core Vector Regression for very large regression problems
    Download  www.cse.ust.hk
    In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
    Ivor W. Tsang, James T. Kwok, Kimo T. Lai
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