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    ESANN
    2008
    112views Neural Networks» more  ESANN 2008»
    Homogeneous bipartition based on multidimensional ranking
    13 years 11 months ago
    Homogeneous bipartition based on multidimensional ranking
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    We present an algorithm which partitions a data set in two parts with equal size and experimentally nearly the same distribution measured through the likelihood of a Parzen kernel ...
    Michaël Aupetit
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    ESANN
    2008
    210views Neural Networks» more  ESANN 2008»
    Petri nets design based on neural networks
    13 years 11 months ago
    Petri nets design based on neural networks
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    Petri net faulty models are useful for reliability analysis and fault diagnosis of discrete event systems. Such models are difficult to work out as long as they must be computed ac...
    Edouard Leclercq, Souleiman Ould el Medhi, Dimitri...
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    ESANN
    2008
    127views Neural Networks» more  ESANN 2008»
    Using graph-theoretic measures to predict the performance of associative memory models
    13 years 11 months ago
    Using graph-theoretic measures to predict the performance of associative memory models
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    We test a selection of associative memory models built with different connection strategies, exploring the relationship between the structural properties of each network and its pa...
    Lee Calcraft, Rod Adams, Weiliang Chen, Neil Davey
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    ESANN
    2008
    116views Neural Networks» more  ESANN 2008»
    Rank-based quality assessment of nonlinear dimensionality reduction
    13 years 11 months ago
    Rank-based quality assessment of nonlinear dimensionality reduction
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    Abstract. Nonlinear dimensionality reduction aims at providing lowdimensional representions of high-dimensional data sets. Many new methods have been proposed in the recent years, ...
    John Aldo Lee, Michel Verleysen
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    ESANN
    2008
    188views Neural Networks» more  ESANN 2008»
    An emphasized target smoothing procedure to improve MLP classifiers performance
    13 years 11 months ago
    An emphasized target smoothing procedure to improve MLP classifiers performance
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    Standard learning procedures are better fitted to estimation than to classification problems, and focusing the training on appropriate samples provides performance advantages in cl...
    Soufiane El Jelali, Abdelouahid Lyhyaoui, An&iacut...
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    ESANN
    2008
    107views Neural Networks» more  ESANN 2008»
    The gamma cycle and its role in the formation of assemblies
    13 years 11 months ago
    The gamma cycle and its role in the formation of assemblies
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    Rhythmic synchronization of activated neural groups in the gamma-frequency range (30-100 Hz) is observed in many brain regions. Interneuron networks are key to the generation of th...
    Thomas Burwick
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    ESANN
    2008
    107views Neural Networks» more  ESANN 2008»
    On related violating pairs for working set selection in SMO algorithms
    13 years 11 months ago
    On related violating pairs for working set selection in SMO algorithms
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    Sequential Minimal Optimization (SMO) is currently the most popular algorithm to solve large quadratic programs for Support Vector Machine (SVM) training. For many variants of this...
    Tobias Glasmachers
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    ESANN
    2008
    117views Neural Networks» more  ESANN 2008»
    Computationally Efficient Neural Field Dynamics
    13 years 11 months ago
    Computationally Efficient Neural Field Dynamics
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    We propose a modification of the dynamic neural field model of Amari [1], aiming at reducing the simulation effort by employing spaceand frequency representations of the dynamic st...
    Alexander Gepperth, Jannik Fritsch, Christian Goer...
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    ESANN
    2008
    143views Neural Networks» more  ESANN 2008»
    An FPGA-based model suitable for evolution and development of spiking neural networks
    13 years 11 months ago
    An FPGA-based model suitable for evolution and development of spiking neural networks
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    We propose a digital neuron model suitable for evolving and growing heterogeneous spiking neural networks on FPGAs using a piecewise linear approximation of the Quadratic Integrate...
    Hooman Shayani, Peter J. Bentley, Andrew M. Tyrrel...
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    ESANN
    2008
    129views Neural Networks» more  ESANN 2008»
    Pruning and Regularisation in Reservoir Computing: a First Insight
    13 years 11 months ago
    Pruning and Regularisation in Reservoir Computing: a First Insight
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    Reservoir Computing is a new paradigm for using Recurrent Neural Networks which shows promising results. However, as the recurrent part is created randomly, it typically needs to b...
    Xavier Dutoit, Benjamin Schrauwen, Jan M. Van Camp...
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