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    GECCO
    2005
    Springer
    195views Optimization» more  GECCO 2005»
    Evolutionary strategies for multi-scale radial basis function kernels in support vector machines
    13 years 11 months ago
    Evolutionary strategies for multi-scale radial basis function kernels in support vector machines
    Download  www.cs.bham.ac.uk
    In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suit...
    Tanasanee Phienthrakul, Boonserm Kijsirikul
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    AMC
    2006
    125views more  AMC 2006»
    A symbolic and algebraic computation based Lambda-Boolean reduction machine via PROLOG
    13 years 5 months ago
    A symbolic and algebraic computation based Lambda-Boolean reduction machine via PROLOG
    Download  w3.gazi.edu.tr
    This paper presents a new Lambda-Boolean reduction machine for Lambda-Boolean and Lambda-Beta Boolean reductions in the context of Lambda Calculus and introduces the role of Churc...
    Seref Mirasyedioglu, Tolga Güyer
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    ICANN
    2005
    Springer
    235views Neural Networks» more  ICANN 2005»
    Training of Support Vector Machines with Mahalanobis Kernels
    13 years 11 months ago
    Training of Support Vector Machines with Mahalanobis Kernels
    Download  www.lib.kobe-u.ac.jp
    Abstract. Radial basis function (RBF) kernels are widely used for support vector machines. But for model selection, we need to optimize the kernel parameter and the margin paramete...
    Shigeo Abe
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    ISNN
    2005
    Springer
    132views Neural Networks» more  ISNN 2005»
    Scaling the Kernel Function to Improve Performance of the Support Vector Machine
    13 years 11 months ago
    Scaling the Kernel Function to Improve Performance of the Support Vector Machine
    Download  www.dcs.warwick.ac.uk
    Abstract. The present study investigates a geometrical method for optimizing the kernel function of a support vector machine. The method is an improvement of the one proposed in [4...
    Peter Williams, Sheng Li, Jianfeng Feng, Si Wu
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    ADCM
    2006
    74views more  ADCM 2006»
    Linearly constrained reconstruction of functions by kernels with applications to machine learning
    13 years 5 months ago
    Linearly constrained reconstruction of functions by kernels with applications to machine learning
    Download  num.math.uni-goettingen.de
    This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
    Robert Schaback, J. Werner
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