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    ICONIP
    2007
    97views Information Technology» more  ICONIP 2007»
    Using Generalization Error Bounds to Train the Set Covering Machine
    13 years 9 months ago
    Using Generalization Error Bounds to Train the Set Covering Machine
    Download  eprints.pascal-network.org
    In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...
    Zakria Hussain, John Shawe-Taylor
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    ESANN
    2007
    112views Neural Networks» more  ESANN 2007»
    Model Selection for Kernel Probit Regression
    13 years 9 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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    ANNS
    2007
    122views Neural Networks» more  ANNS 2007»
    Direct and indirect classification of high-frequency LNA performance using machine learning techniques
    13 years 9 months ago
    Direct and indirect classification of high-frequency LNA performance using machine learning techniques
    Download  eprints.nuim.ie
    The task of determining low noise amplifier (LNA) high-frequency performance in functional testing is as challenging as designing the circuit itself due to the difficulties associa...
    Peter C. Hung, Seán F. McLoone, Magdalena S...
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    BMCBI
    2006
    121views more  BMCBI 2006»
    Splice site identification using probabilistic parameters and SVM classification
    13 years 7 months ago
    Splice site identification using probabilistic parameters and SVM classification
    Download  www.biomedcentral.com
    Background: Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and ...
    A. K. M. A. Baten, Bill C. H. Chang, Saman K. Halg...
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    IJCNN
    2007
    IEEE
    222views Neural Networks» more  IJCNN 2007»
    Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
    14 years 2 months ago
    Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
    Download  theoval.cmp.uea.ac.uk
    Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
    Gavin C. Cawley, Nicola L. C. Talbot
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