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    CIBCB
    2008
    IEEE
    163views Computational Biology» more  CIBCB 2008»
    Classification of mouse fRNA genes using evolved neural networks
    14 years 3 months ago
    Classification of mouse fRNA genes using evolved neural networks
    Download  65.44.200.132
    Functional RNAs (fRNAs) play a key role in gene regulation, at both the transcriptional and translational levels. Identification of fRNA genes can be difficult, given that some cla...
    Mars Cheung, Gary B. Fogel
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    CIBCB
    2005
    IEEE
    86views Computational Biology» more  CIBCB 2005»
    Identification of Functional RNA Genes Using Evolved Neural Networks
    14 years 2 months ago
    Identification of Functional RNA Genes Using Evolved Neural Networks
    Download  65.44.200.132
    Functional RNAs (fRNAs) play a key role in gene regulation, at both the transcriptional and translational levels. Identification of fRNA genes can be difficult, given that some cla...
    Mars Cheung, Gary B. Fogel
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    ESANN
    2003
    124views Neural Networks» more  ESANN 2003»
    Neural networks organizations to learn complex robotic functions
    13 years 10 months ago
    Neural networks organizations to learn complex robotic functions
    Download  www.dice.ucl.ac.be
    Abstract. This paper considers the general problem of function estimation with a modular approach of neural computing. We propose to use functionally independent subnetworks to lea...
    Gilles Hermann, Patrice Wira, Jean-Philippe Urban
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    NIPS
    1996
    144views Information Technology» more  NIPS 1996»
    Effective Training of a Neural Network Character Classifier for Word Recognition
    13 years 10 months ago
    Effective Training of a Neural Network Character Classifier for Word Recognition
    Download  www.beanblossom.in.us
    We have combined an artificial neural network (ANN) character classifier with context-driven search over character segmentation, word segmentation, and word recognition hypotheses...
    Larry S. Yaeger, Richard F. Lyon, Brandyn J. Webb
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    JMLR
    2006
    389views more  JMLR 2006»
    A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
    13 years 8 months ago
    A Very Fast Learning Method for Neural Networks Based on Sensitivity Analysis
    Download  jmlr.csail.mit.edu
    This paper introduces a learning method for two-layer feedforward neural networks based on sensitivity analysis, which uses a linear training algorithm for each of the two layers....
    Enrique Castillo, Bertha Guijarro-Berdiñas,...
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