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    ESANN
    2006
    110views Neural Networks» more  ESANN 2006»
    Designing neural network committees by combining boosting ensembles
    13 years 9 months ago
    Designing neural network committees by combining boosting ensembles
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    The use of modified Real Adaboost ensembles by applying weighted emphasis on erroneous and critical (near the classification boundary) has been shown to lead to improved designs, ...
    Vanessa Gómez-Verdejo, Aníbal R. Fig...
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    ESANN
    2006
    117views Neural Networks» more  ESANN 2006»
    Extended model of conditioned learning within latent inhibition
    13 years 9 months ago
    Extended model of conditioned learning within latent inhibition
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    Due to the various and dynamic nature of stimuli, decisions of intelligent agents must rely on the coordination of complex cognitive systems. This paper precisely focusses on a gen...
    Nicolas Gomond, Jean Marc Salotti
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    ESANN
    2006
    179views Neural Networks» more  ESANN 2006»
    Visual nonlinear discriminant analysis for classifier design
    13 years 9 months ago
    Visual nonlinear discriminant analysis for classifier design
    Download  www.kecl.ntt.co.jp
    Abstract. We present a new method for analyzing classifiers by visualization, which we call visual nonlinear discriminant analysis. Classifiers that output posterior probabilities ...
    Tomoharu Iwata, Kazumi Saito, Naonori Ueda
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    ESANN
    2006
    84views Neural Networks» more  ESANN 2006»
    Spatial filters for the classification of event-related potentials
    13 years 9 months ago
    Spatial filters for the classification of event-related potentials
    Download  www.dice.ucl.ac.be
    Spatial filtering is a widely used dimension reduction method in electroencephalogram based brain-computer interface systems. In this paper a new algorithm is proposed, which learn...
    Ulrich Hoffmann, Jean-Marc Vesin, Touradj Ebrahimi
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    ESANN
    2006
    164views Neural Networks» more  ESANN 2006»
    A Gaussian process latent variable model formulation of canonical correlation analysis
    13 years 9 months ago
    A Gaussian process latent variable model formulation of canonical correlation analysis
    Download  www.dice.ucl.ac.be
    Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
    Gayle Leen, Colin Fyfe
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