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    NIPS
    2008
    210views Information Technology» more  NIPS 2008»
    Non-stationary dynamic Bayesian networks
    13 years 9 months ago
    Non-stationary dynamic Bayesian networks
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    Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
    Joshua W. Robinson, Alexander J. Hartemink
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    ECCV
    2008
    Springer
    220views Computer Vision» more  ECCV 2008»
    Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
    14 years 9 months ago
    Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
    Download  www.ecse.rpi.edu
    Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
    Cassio Polpo de Campos, Yan Tong, Qiang Ji
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    ACL
    2007
    110views Computational Linguistics» more  ACL 2007»
    Much ado about nothing: A social network model of Russian paradigmatic gaps
    13 years 9 months ago
    Much ado about nothing: A social network model of Russian paradigmatic gaps
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    A number of Russian verbs lack 1sg nonpast forms. These paradigmatic gaps are puzzling because they seemingly contradict the highly productive nature of inflectional systems. We m...
    Robert Daland, Andrea D. Sims, Janet Pierrehumbert
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    BMCBI
    2011
    252views Artificial Intelligence» more  BMCBI 2011»
    A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
    12 years 11 months ago
    A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-w
    Download  www.biomedcentral.com
    Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
    Raphael Mourad, Christine Sinoquet, Philippe Leray
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    KES
    2007
    Springer
    102views Information Technology» more  KES 2007»
    Predictive and Contextual Feature Separation for Bayesian Metanetworks
    14 years 1 months ago
    Predictive and Contextual Feature Separation for Bayesian Metanetworks
    Download  www.cs.jyu.fi
    Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
    Vagan Y. Terziyan
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