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    ESANN
    2004
    231views Neural Networks» more  ESANN 2004»
    Neural networks for data mining: constrains and open problems
    14 years 29 days ago
    Neural networks for data mining: constrains and open problems
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    When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
    Razvan Andonie, Boris Kovalerchuk
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    ESANN
    2004
    144views Neural Networks» more  ESANN 2004»
    An informational energy LVQ approach for feature ranking
    14 years 29 days ago
    An informational energy LVQ approach for feature ranking
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    Input feature ranking and selection represent a necessary preprocessing stage in classification, especially when one is required to manage large quantities of data. We introduce a ...
    Razvan Andonie, Angel Cataron
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    ESANN
    2004
    87views Neural Networks» more  ESANN 2004»
    A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm
    14 years 29 days ago
    A New Learning Rates Adaptation Strategy for the Resilient Propagation Algorithm
    Download  www.dice.ucl.ac.be
    In this paper we propose an Rprop modification that builds on a mathematical framework for the convergence analysis to equip Rprop with a learning rates adaptation strategy that en...
    Aristoklis D. Anastasiadis, George D. Magoulas, Mi...
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    ESANN
    2004
    115views Neural Networks» more  ESANN 2004»
    Input arrival-time-dependent decoding scheme for a spiking neural network
    14 years 29 days ago
    Input arrival-time-dependent decoding scheme for a spiking neural network
    Download  www.dice.ucl.ac.be
    Spiking neurons model a type of biological neural system where information is encoded with spike times. In this paper, a new method for decoding input spikes according to their abs...
    Hesham H. Amin, Robert H. Fujii
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    ESANN
    2004
    92views Neural Networks» more  ESANN 2004»
    Lattice ICA for the separation of speech signals
    14 years 29 days ago
    Lattice ICA for the separation of speech signals
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    This work explains a method for blind separation of a linear mixture of sources, through geometrical considerations concerning the scatter plot. This method is applied to a mixture...
    Manuel Rodríguez Álvarez, Fernando R...
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    ESANN
    2004
    83views Neural Networks» more  ESANN 2004»
    Shear strength prediction using dimensional analysis and functional networks
    14 years 29 days ago
    Shear strength prediction using dimensional analysis and functional networks
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    This paper presents a three steps methodology for predicting the failure shear effort in concrete beams. In the first step, dimensional analysis is applied to obtain several sets o...
    Amparo Alonso-Betanzos, Enrique Castillo, Oscar Fo...
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    ESANN
    2004
    165views Neural Networks» more  ESANN 2004»
    Robust Bayesian Mixture Modelling
    14 years 29 days ago
    Robust Bayesian Mixture Modelling
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    Abstract. Bayesian approaches to density estimation and clustering using mixture distributions allow the automatic determination of the number of components in the mixture. Previou...
    Christopher M. Bishop, Markus Svensén
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    ESANN
    2004
    92views Neural Networks» more  ESANN 2004»
    Fuzzy LP-SVMs for Multiclass Problems
    14 years 29 days ago
    Fuzzy LP-SVMs for Multiclass Problems
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    Abstract. In this paper, we propose fuzzy linear programming support vector machines (LP-SVMs) that resolve unclassifiable regions for multiclass problems. Namely, in the direction...
    Shigeo Abe
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    ESANN
    2004
    124views Neural Networks» more  ESANN 2004»
    Description of the Group Dynamic of Funds' Managers using Kohonen's Map
    14 years 29 days ago
    Description of the Group Dynamic of Funds' Managers using Kohonen's Map
    Download  www.dice.ucl.ac.be
    : the aim of this paper is to observe the group dynamic of funds' managers during an interesting period : January 99- July 01, which includes many financial events as financia...
    Catherine Aaron, Yamina Tadjeddine
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    ESANN
    2007
    187views Neural Networks» more  ESANN 2007»
    How to process uncertainty in machine learning?
    14 years 1 months ago
    How to process uncertainty in machine learning?
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    Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
    Barbara Hammer, Thomas Villmann
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