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    ESANN
    2006
    149views Neural Networks» more  ESANN 2006»
    Lag selection for regression models using high-dimensional mutual information
    14 years 28 days ago
    Lag selection for regression models using high-dimensional mutual information
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    Mutual information may be used to select the embedding lag of a time series. However, this lag selection is usually limited to the analysis of the mutual information between a pair...
    Geoffroy Simon, Michel Verleysen
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    ESANN
    2006
    137views Neural Networks» more  ESANN 2006»
    Neural networks and machine learning in bioinformatics - theory and applications
    14 years 28 days ago
    Neural networks and machine learning in bioinformatics - theory and applications
    Download  www.dice.ucl.ac.be
    Bioinformatics is a promising and innovative research field. Despite of a high number of techniques specifically dedicated to bioinformatics problems as well as many successful app...
    Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas...
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    ESANN
    2006
    134views Neural Networks» more  ESANN 2006»
    Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic
    14 years 28 days ago
    Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic
    Download  www.dice.ucl.ac.be
    Abstract. Current digital, directly mapped implementations of spiking neural networks use serial processing and parallel arithmetic. On a standard CPU, this might be the good choic...
    Benjamin Schrauwen, Jan M. Van Campenhout
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    ESANN
    2006
    123views Neural Networks» more  ESANN 2006»
    Linking non-binned spike train kernels to several existing spike train metrics
    14 years 28 days ago
    Linking non-binned spike train kernels to several existing spike train metrics
    Download  www.dice.ucl.ac.be
    This work presents two kernels which can be applied to sets of spike times. This allows the use of state-of-the-art classification techniques to spike trains. The presented kernels...
    Benjamin Schrauwen, Jan M. Van Campenhout
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    ESANN
    2006
    161views Neural Networks» more  ESANN 2006»
    OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method
    14 years 28 days ago
    OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method
    Download  www.dice.ucl.ac.be
    Abstract. We present the OnlineDoubleMaxMinOver approach to obtain the Support Vectors in two class classification problems. With its linear time complexity and linear convergence ...
    Daniel Schneegaß, Thomas Martinetz, Michael ...
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    ESANN
    2006
    144views Neural Networks» more  ESANN 2006»
    Evolino for recurrent support vector machines
    14 years 28 days ago
    Evolino for recurrent support vector machines
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    Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
    Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...
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    ESANN
    2006
    192views Neural Networks» more  ESANN 2006»
    Margin based Active Learning for LVQ Networks
    14 years 28 days ago
    Margin based Active Learning for LVQ Networks
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    In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
    Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
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    ESANN
    2006
    129views Neural Networks» more  ESANN 2006»
    Iterative context compilation for visual object recognition
    14 years 28 days ago
    Iterative context compilation for visual object recognition
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    This contribution describes an almost parameterless iterative context compilation method, which produces feature layers, that are especially suited for mixed bottom-up top-down ass...
    Jens Teichert, Rainer Malaka
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    ESANN
    2006
    202views Neural Networks» more  ESANN 2006»
    Data topology visualization for the Self-Organizing Map
    14 years 28 days ago
    Data topology visualization for the Self-Organizing Map
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    The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
    Kadim Tasdemir, Erzsébet Merényi
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    ESANN
    2006
    116views Neural Networks» more  ESANN 2006»
    Nonlinear dynamics in neural computation
    14 years 28 days ago
    Nonlinear dynamics in neural computation
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    This tutorial reports on the use of nonlinear dynamics in several different models of neural systems. We discuss a number of distinct approaches to neural information processing ba...
    Tjeerd Olde Scheper, Nigel Crook
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