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    COLING
    1996
    92views Computational Linguistics» more  COLING 1996»
    FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
    13 years 9 months ago
    FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
    Download  acl.ldc.upenn.edu
    We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
    Finn Dag Buø, Alex Waibel
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    GECCO
    2006
    Springer
    208views Optimization» more  GECCO 2006»
    Comparing evolutionary and temporal difference methods in a reinforcement learning domain
    13 years 11 months ago
    Comparing evolutionary and temporal difference methods in a reinforcement learning domain
    Download  www.cs.bham.ac.uk
    Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
    Matthew E. Taylor, Shimon Whiteson, Peter Stone
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    ICONIP
    1998
    147views Information Technology» more  ICONIP 1998»
    Inducing Relational Concepts with Neural Networks via the LINUS System
    13 years 9 months ago
    Inducing Relational Concepts with Neural Networks via the LINUS System
    Download  www.soi.city.ac.uk
    This paper presents a method to induce relational concepts with neural networks using the inductive logic programming system LINUS. Some first-order inductive learning tasks taken...
    Rodrigo Basilio, Gerson Zaverucha, Artur S. d'Avil...
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    IJCAI
    2001
    118views Artificial Intelligence» more  IJCAI 2001»
    Neural Logic Network Learning using Genetic Programming
    13 years 9 months ago
    Neural Logic Network Learning using Genetic Programming
    Download  www.comp.nus.edu.sg
    Neural Logic Network or Neulonet is a hybrid of neural network expert systems. Its strength lies in its ability to learn and to represent human logic in decision making using comp...
    Chew Lim Tan, Henry Wai Kit Chia
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    HIS
    2008
    157views Information Technology» more  HIS 2008»
    Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
    13 years 9 months ago
    Bio-Inspired Parameter Tunning of MLP Networks for Gene Expression Analysis
    Download  www.liaad.up.pt
    The performance of Artificial Neural Networks is largely influenced by the value of their parameters. Among these free parameters, one can mention those related with the network a...
    André L. D. Rossi, André C. P. L. F....
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