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    ESANN
    2008
    115views Neural Networks» more  ESANN 2008»
    Similarities and differences between policy gradient methods and evolution strategies
    13 years 6 months ago
    Similarities and differences between policy gradient methods and evolution strategies
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    Natural policy gradient methods and the covariance matrix adaptation evolution strategy, two variable metric methods proposed for solving reinforcement learning tasks, are contrast...
    Verena Heidrich-Meisner, Christian Igel
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    ESANN
    2008
    104views Neural Networks» more  ESANN 2008»
    The impact of axon wiring costs on small neuronal networks
    13 years 6 months ago
    The impact of axon wiring costs on small neuronal networks
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    Recent papers by D. Chklovskii and E.M. Izhikevich suggest that wiring costs may play a significant role in the physical layout and function of neuronal structures. About eighty ye...
    Conrad Attard, Andreas Alexander Albrecht
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    ESANN
    2008
    103views Neural Networks» more  ESANN 2008»
    Selection of important input variables for RBF network using partial derivatives
    13 years 6 months ago
    Selection of important input variables for RBF network using partial derivatives
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    In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
    Jarkko Tikka, Jaakko Hollmén
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    ESANN
    2008
    163views Neural Networks» more  ESANN 2008»
    Clustering of Self-Organizing Map
    13 years 6 months ago
    Clustering of Self-Organizing Map
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    Abstract. In this paper, we present a new similarity measure for a clustering self-organizing map which will be reached using a new approach of hierarchical clustering. (1) The sim...
    Hanane Azzag, Mustapha Lebbah
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    ESANN
    2008
    150views Neural Networks» more  ESANN 2008»
    Conditional prediction of time series using spiral recurrent neural network
    13 years 6 months ago
    Conditional prediction of time series using spiral recurrent neural network
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    Frequently, sequences of state transitions are triggered by specific signals. Learning these triggered sequences with recurrent neural networks implies storing them as different at...
    Huaien Gao, Rudolf Sollacher
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    ESANN
    2008
    149views Neural Networks» more  ESANN 2008»
    Detecting zebra crossings utilizing AdaBoost
    13 years 6 months ago
    Detecting zebra crossings utilizing AdaBoost
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    This paper introduces a visual zebra crossing detector based on the Viola-Jones approach. The basic properties of this cascaded classifier and the use of integral images are explai...
    Ludwig Lausser, Friedhelm Schwenker, Günther ...
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    ESANN
    2008
    133views Neural Networks» more  ESANN 2008»
    Linear Projection based on Noise Variance Estimation - Application to Spectral Data
    13 years 6 months ago
    Linear Projection based on Noise Variance Estimation - Application to Spectral Data
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    In this paper, we propose a new methodology to build latent variables that are optimal if a nonlinear model is used afterward. This method is based on Nonparametric Noise Estimatio...
    Amaury Lendasse, Francesco Corona
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    ESANN
    2008
    137views Neural Networks» more  ESANN 2008»
    Classification of chestnuts with feature selection by noise resilient classifiers
    13 years 6 months ago
    Classification of chestnuts with feature selection by noise resilient classifiers
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    In this paper we solve the problem of classifying chestnut plants according to their place of origin. We compare the results obtained by state of the art classifiers, among which,...
    Elena Roglia, Rossella Cancelliere, Rosa Meo
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    ESANN
    2008
    91views Neural Networks» more  ESANN 2008»
    Phase transitions in Vector Quantization
    13 years 6 months ago
    Phase transitions in Vector Quantization
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    Abstract. We study Winner-Takes-All and rank based Vector Quantization along the lines of the statistical physics of off-line learning. Typical behavior of the system is obtained w...
    Aree Witoelar, Anarta Ghosh, Michael Biehl
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    ESANN
    2008
    121views Neural Networks» more  ESANN 2008»
    A neural model with feedback for robust disambiguation of motion
    13 years 6 months ago
    A neural model with feedback for robust disambiguation of motion
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    Abstract. The aperture problem is a direct consequence of any local detection in the visual perception of motion. It results in ambiguous responses of the local motion detectors. B...
    Mauricio Cerda, Bernard Girau
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