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    AIED
    2005
    Springer
    106views Artificial Intelligence» more  AIED 2005»
    Inferring learning and attitudes from a Bayesian Network of log file data
    14 years 4 months ago
    Inferring learning and attitudes from a Bayesian Network of log file data
    Download  althea.cs.umass.edu
    A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and hel...
    Ivon Arroyo, Beverly Park Woolf
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    IDA
    2003
    Springer
    119views Information Technology» more  IDA 2003»
    Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
    14 years 4 months ago
    Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
    Download  people.brunel.ac.uk
    Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
    Allan Tucker, Xiaohui Liu
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    IJAR
    2010
    74views more  IJAR 2010»
    On the robustness of Bayesian networks to learning from non-conjugate sampling
    13 years 9 months ago
    On the robustness of Bayesian networks to learning from non-conjugate sampling
    Download  www2.warwick.ac.uk
    Jim Q. Smith, Alireza Daneshkhah
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    IJAR
    2006
    89views more  IJAR 2006»
    Learning probabilistic decision graphs
    13 years 11 months ago
    Learning probabilistic decision graphs
    Download  www.cs.aau.dk
    Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
    Manfred Jaeger, Jens D. Nielsen, Tomi Silander
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    GECCO
    2007
    Springer
    558views Optimization» more  GECCO 2007»
    A chain-model genetic algorithm for Bayesian network structure learning
    14 years 5 months ago
    A chain-model genetic algorithm for Bayesian network structure learning
    Download  www.cs.bham.ac.uk
    Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
    Ratiba Kabli, Frank Herrmann, John McCall
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