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    ESANN
    2008
    112views Neural Networks» more  ESANN 2008»
    K-nearest neighbours based on mutual information for incomplete data classification
    13 years 6 months ago
    K-nearest neighbours based on mutual information for incomplete data classification
    Download  www.dice.ucl.ac.be
    Incomplete data is a common drawback that machine learning techniques need to deal with when solving real-life classification tasks. One of the most popular procedures for solving ...
    Pedro J. García-Laencina, José-Luis ...
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    ESANN
    2008
    142views Neural Networks» more  ESANN 2008»
    Simulation of a recurrent neurointerface with sparse electrical connections
    13 years 6 months ago
    Simulation of a recurrent neurointerface with sparse electrical connections
    Download  www.dice.ucl.ac.be
    With the technical development of multi-electrode arrays, the monitoring of many individual neurons has become feasible. However, for practical use of those arrays as bidirectional...
    Andreas Herzog, Karsten Kube, Bernd Michaelis, Ana...
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    ESANN
    2007
    144views Neural Networks» more  ESANN 2007»
    Mixtures of robust probabilistic principal component analyzers
    13 years 6 months ago
    Mixtures of robust probabilistic principal component analyzers
    Download  www.dice.ucl.ac.be
    Mixtures of probabilistic principal component analyzers model high-dimensional nonlinear data by combining local linear models. Each mixture component is specifically designed to...
    Cédric Archambeau, Nicolas Delannay, Michel...
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    ESANN
    2007
    113views Neural Networks» more  ESANN 2007»
    Kernel-based online machine learning and support vector reduction
    13 years 6 months ago
    Kernel-based online machine learning and support vector reduction
    Download  www.physics.ox.ac.uk
    We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online meth...
    Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick
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    ESANN
    2008
    90views Neural Networks» more  ESANN 2008»
    Comparison of sparse least squares support vector regressors trained in primal and dual
    13 years 6 months ago
    Comparison of sparse least squares support vector regressors trained in primal and dual
    Download  www.dice.ucl.ac.be
    In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this p...
    Shigeo Abe
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