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    ESANN
    2004
    163views Neural Networks» more  ESANN 2004»
    Neural methods for non-standard data
    14 years 29 days ago
    Neural methods for non-standard data
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    Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
    Barbara Hammer, Brijnesh J. Jain
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    ESANN
    2004
    87views Neural Networks» more  ESANN 2004»
    A VLSI reconfigurable network of integrate-and-fire neurons with spike-based learning synapses
    14 years 29 days ago
    A VLSI reconfigurable network of integrate-and-fire neurons with spike-based learning synapses
    Download  www.ini.uzh.ch
    Giacomo Indiveri, Elisabetta Chicca, Rodney J. Dou...
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    ESANN
    2004
    133views Neural Networks» more  ESANN 2004»
    Dimensionality reduction and classification using the distribution mapping exponent
    14 years 29 days ago
    Dimensionality reduction and classification using the distribution mapping exponent
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    : Probability distribution mapping function, which maps multivariate data distribution to the function of one variable, is introduced. Distributionmapping exponent (DME) is somethi...
    Marcel Jirina
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    ESANN
    2004
    109views Neural Networks» more  ESANN 2004»
    On-line support vector machines and optimization strategies
    14 years 29 days ago
    On-line support vector machines and optimization strategies
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    Juan Manuel Górriz, Carlos García Pu...
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    ESANN
    2004
    112views Neural Networks» more  ESANN 2004»
    A Modular Framework for Multi category feature selection in Digital mammography
    14 years 29 days ago
    A Modular Framework for Multi category feature selection in Digital mammography
    Download  www.dice.ucl.ac.be
    Many existing researches utilized many different approaches for recognition in digital mammography using various ANN classifier-modeling techniques. Different types of feature extr...
    Ranadhir Ghosh, Moumita Ghosh, John Yearwood
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    ESANN
    2004
    115views Neural Networks» more  ESANN 2004»
    Non-Euclidean norms and data normalisation
    14 years 29 days ago
    Non-Euclidean norms and data normalisation
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    Kevin Doherty, Rod Adams, Neil Davey
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    ESANN
    2004
    97views Neural Networks» more  ESANN 2004»
    Using Andrews Curves for Clustering and Sub-clustering Self-Organizing Maps
    14 years 29 days ago
    Using Andrews Curves for Clustering and Sub-clustering Self-Organizing Maps
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    Abstract. The use of self-organizing maps to analyze data often depends on finding effective methods to visualize the SOM's structure. In this paper we propose a new way to pe...
    Cesar García-Osorio, Jesús Maudes, C...
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    ESANN
    2004
    90views Neural Networks» more  ESANN 2004»
    Functional radial basis function networks
    14 years 29 days ago
    Functional radial basis function networks
    Download  apiacoa.org
    There has been recently a lot of interest for functional data analysis [1] and extensions of well-known methods to functional inputs (clustering algorithm [2], non-parametric model...
    Nicolas Delannay, Fabrice Rossi, Brieuc Conan-Guez...
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    ESANN
    2004
    160views Neural Networks» more  ESANN 2004»
    Evolutionary tuning of multiple SVM parameters
    14 years 29 days ago
    Evolutionary tuning of multiple SVM parameters
    Download  www.neuroinformatik.ruhr-uni-bochum.de
    The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matr...
    Frauke Friedrichs, Christian Igel
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    ESANN
    2004
    90views Neural Networks» more  ESANN 2004»
    High-accuracy value-function approximation with neural networks applied to the acrobot
    14 years 29 days ago
    High-accuracy value-function approximation with neural networks applied to the acrobot
    Download  remi.coulom.free.fr
    Several reinforcement-learning techniques have already been applied to the Acrobot control problem, using linear function approximators to estimate the value function. In this pape...
    Rémi Coulom
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