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    NAACL
    2003
    152views Computational Linguistics» more  NAACL 2003»
    Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
    15 years 8 months ago
    Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
    Download  acl.ldc.upenn.edu
    This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
    Shona Douglas
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    ESANN
    1998
    142views Neural Networks» more  ESANN 1998»
    Lazy learning for control design
    15 years 8 months ago
    Lazy learning for control design
    Download  www.dice.ucl.ac.be
    This paper presents two local methods for the control of discrete-time unknown nonlinear dynamical systems, when only a limited amount of input-output data is available. The modeli...
    Gianluca Bontempi, Mauro Birattari, Hugues Bersini
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    CONSTRAINTS
    2008
    89views more  CONSTRAINTS 2008»
    A Reinforcement Learning Approach to Interval Constraint Propagation
    15 years 6 months ago
    A Reinforcement Learning Approach to Interval Constraint Propagation
    Download  www.crt.umontreal.ca
    When solving systems of nonlinear equations with interval constraint methods, it has often been observed that many calls to contracting operators do not participate actively to th...
    Frédéric Goualard, Christophe Jerman...
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    BMCBI
    2005
    153views more  BMCBI 2005»
    Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text
    15 years 6 months ago
    Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text
    Download  pages.cs.wisc.edu
    Background: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical ...
    Soumya Ray, Mark Craven
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    ICASSP
    2011
    IEEE
    199views Signal Processing» more  ICASSP 2011»
    Low-rank matrix completion by variational sparse Bayesian learning
    14 years 10 months ago
    Low-rank matrix completion by variational sparse Bayesian learning
    Download  mirlab.org
    There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
    S. Derin Babacan, Martin Luessi, Rafael Molina, Ag...
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