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    EUSFLAT
    2003
    132views Fuzzy Logic» more  EUSFLAT 2003»
    Modeling high interest areas in descriptive TS fuzzy rule based systems
    15 years 5 months ago
    Modeling high interest areas in descriptive TS fuzzy rule based systems
    Download  www.eusflat.org
    A descriptive Takagi-Sugeno fuzzy rule based system suffers under the curse of dimensionality since the number of rules is equal to a fuzzy system with a fully filled up decision...
    Ingo Renners, Adolf Grauel
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    138
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    NAACL
    2001
    130views Computational Linguistics» more  NAACL 2001»
    Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
    15 years 5 months ago
    Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
    Download  www.aclweb.org
    Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develo...
    Renaud Lecoeuche
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    155
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    DAGSTUHL
    2000
    152views Software Engineering» more  DAGSTUHL 2000»
    Vision and Touch for Grasping
    15 years 5 months ago
    Vision and Touch for Grasping
    Download  www.neuroinformatik.ruhr-uni-bochum.de
    This paper introduces our one-armed stationary humanoid robot GripSee together with research projects carried out on this platform. The major goal is to have it analyze a table sce...
    Rolf P. Würtz
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    147
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    ASC
    2008
    123views Artificial Intelligence» more  ASC 2008»
    Evolving a Bayesian classifier for ECG-based age classification in medical applications
    15 years 3 months ago
    Evolving a Bayesian classifier for ECG-based age classification in medical applications
    Download  www.matthewcwiggins.com
    Abstract. Objective: Age classification of patients based on information extracted from electrocardiograms (ECG's). The scope of this work is to develop and compare the perfor...
    M. Wiggins, A. Saad, Brian Litt, George J. Vachtse...
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    164
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    AI
    2006
    Springer
    184views Artificial Intelligence» more  AI 2006»
    Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
    15 years 3 months ago
    Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
    Download  ti.arc.nasa.gov
    This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
    Ole J. Mengshoel, David C. Wilkins, Dan Roth
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