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    ESANN
    2003
    65views Neural Networks» more  ESANN 2003»
    Robust Topology Representing Networks
    14 years 7 days ago
    Robust Topology Representing Networks
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    Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
    Michaël Aupetit
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    ESANN
    2003
    82views Neural Networks» more  ESANN 2003»
    High-dimensional labeled data analysis with Gabriel graphs
    14 years 7 days ago
    High-dimensional labeled data analysis with Gabriel graphs
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    We propose the use of the Gabriel graph for the exploratory analysis of potentially high dimensional labeled data. Gabriel graph is a subgraph of the Delaunay triangulation, which ...
    Michaël Aupetit
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    ESANN
    2003
    92views Neural Networks» more  ESANN 2003»
    On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
    14 years 7 days ago
    On Convergence Problems of the EM Algorithm for Finite Gaussian Mixtures
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    Efficient probability density function estimation is of primary interest in statistics. A popular approach for achieving this is the use of finite Gaussian mixture models. Based on...
    Cédric Archambeau, John Aldo Lee, Michel Ve...
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    ESANN
    2003
    98views Neural Networks» more  ESANN 2003»
    A Fuzzy ARTMAP Probability Estimator with Relevance Factor
    14 years 7 days ago
    A Fuzzy ARTMAP Probability Estimator with Relevance Factor
    Download  www.dice.ucl.ac.be
    Abstract. An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzz...
    Razvan Andonie, Lucian Sasu
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    ESANN
    2003
    85views Neural Networks» more  ESANN 2003»
    The hypersphere neuron
    14 years 7 days ago
    The hypersphere neuron
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    In this paper a special higher order neuron, the hypersphere neuron, is introduced. By embedding Euclidean space in a conformal space, hyperspheres can be expressed as vectors. The...
    Vladimir Banarer, Christian Perwass, Gerald Sommer
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    ESANN
    2003
    136views Neural Networks» more  ESANN 2003»
    Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
    14 years 7 days ago
    Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
    Download  www.dice.ucl.ac.be
    : In flood management it is important to reliably estimate the discharge in a river. Hydrologists use historic data to establish a rating curve – a relationship between the water...
    Biswanath Bhattacharya, Dimitri P. Solomatine
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