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    ICML
    1995
    IEEE
    123views Machine Learning» more  ICML 1995»
    Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
    14 years 9 months ago
    Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network
    Download  www.cs.utexas.edu
    Understanding high-dimensional real world data usually requires learning the structure of the data space. The structure maycontain high-dimensional clusters that are related in co...
    Justine Blackmore, Risto Miikkulainen
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    ICMLA
    2009
    200views Machine Learning» more  ICMLA 2009»
    Application of Artificial Neural Network (ANN) Method to Exergy Analysis of Thermodynamic Systems
    13 years 6 months ago
    Application of Artificial Neural Network (ANN) Method to Exergy Analysis of Thermodynamic Systems
    Download  bildiri.anadolu.edu.tr
    Exergy is a way to sustainable development and may be defined as the maximum theoretical useful work, while exergy analysis identifies the sources, the magnitude and the causes of...
    Yilmaz Yoru, T. Hikmet Karakoc, Arif Hepbasli
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    IJON
    2006
    79views more  IJON 2006»
    Fast computation with neural oscillators
    13 years 8 months ago
    Fast computation with neural oscillators
    Download  www.mit.edu
    This paper studies new spike-based models for winner-take-all computation and coincidence detection. In both cases, very fast convergence is achieved independent of initial condit...
    Wei Wang 0008, Jean-Jacques E. Slotine
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    IEEEICCI
    2002
    IEEE
    126views Artificial Intelligence» more  IEEEICCI 2002»
    Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
    14 years 1 months ago
    Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
    Download  www.cacs.louisiana.edu
    We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly an...
    Wiphada Wettayaprasit, Chidchanok Lursinsap, Chee-...
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    JMLR
    2008
    188views more  JMLR 2008»
    Maximal Causes for Non-linear Component Extraction
    13 years 8 months ago
    Maximal Causes for Non-linear Component Extraction
    Download  www.gatsby.ucl.ac.uk
    We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
    Jörg Lücke, Maneesh Sahani
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