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    TSMC
    2002
    69views more  TSMC 2002»
    A new learning algorithm for the hierarchical structure learning automata operating in the nonstationary S-model random environm
    13 years 8 months ago
    A new learning algorithm for the hierarchical structure learning automata operating in the nonstationary S-model random environm
    Download  ir.lib.osaka-kyoiku.ac.jp
    An extended algorithm of the relative reward strength algorithm is proposed. It is shown that the proposed algorithm ensures the convergence with probability 1 to the optimal path ...
    Norio Baba, Yoshio Mogami
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    COLT
    2003
    Springer
    172views Machine Learning» more  COLT 2003»
    Learning from Uncertain Data
    14 years 1 months ago
    Learning from Uncertain Data
    Download  www.cs.nyu.edu
    The application of statistical methods to natural language processing has been remarkably successful over the past two decades. But, to deal with recent problems arising in this ...
    Mehryar Mohri
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    AII
    1989
    101views Software Engineering» more  AII 1989»
    Inductive Inference, DFAs, and Computational Complexity
    14 years 14 days ago
    Inductive Inference, DFAs, and Computational Complexity
    Download  www.cs.berkeley.edu
    This paper surveys recent results concerning the inference of deterministic finite automata (DFAs). The results discussed determine the extent to which DFAs can be feasibly inferr...
    Leonard Pitt
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    IEEECIT
    2009
    IEEE
    184views Information Technology» more  IEEECIT 2009»
    Clustering of Software Systems Using New Hybrid Algorithms
    14 years 3 months ago
    Clustering of Software Systems Using New Hybrid Algorithms
    Download  ceit.aut.ac.ir
    —Software clustering is a method for increasing software system understanding and maintenance. Software designers, first use MDG graph to model the structure of software system. ...
    Ali Safari Mamaghani, Mohammad Reza Meybodi
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    AAAI
    2012
    254views Intelligent Agents» more  AAAI 2012»
    Learning Behavior Models for Hybrid Timed Systems
    11 years 10 months ago
    Learning Behavior Models for Hybrid Timed Systems
    Download  www.uni-weimar.de
    A tailored model of a system is the prerequisite for various analysis tasks, such as anomaly detection, fault identification, or quality assurance. This paper deals with the algo...
    Oliver Niggemann, Benno Stein, Asmir Vodencarevic,...
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