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    » Learning Mixtures of DAG Models
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    NIPS
    1998
    117views Information Technology» more  NIPS 1998»
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
    15 years 4 months ago
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
    Download  www.gatsby.ucl.ac.uk
    We present Monte-Carlo generalized EM equations for learning in nonlinear state space models. The dif
    Thomas Briegel, Volker Tresp
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    ICPR
    2008
    IEEE
    152views Computer Vision» more  ICPR 2008»
    Component-wise parameter smoothing for learning mixture models
    16 years 4 months ago
    Component-wise parameter smoothing for learning mixture models
    Download  www.cs.wayne.edu
    In this paper, we propose a novel component-wise smoothing algorithm that constructs a hierarchy (or family) of smoothened log-likelihood surfaces. Our approach first smoothens th...
    Bala Rajaratnam, Chandan K. Reddy
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    VISAPP
    2008
    140views Computer Vision» more  VISAPP 2008»
    Online Learning of Gaussian Mixture Models - a Two-Level Approach
    15 years 5 months ago
    Online Learning of Gaussian Mixture Models - a Two-Level Approach
    Download  www.montefiore.ulg.ac.be
    Arnaud Declercq, Justus H. Piater
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    108
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    IDA
    2010
    Springer
    135views Information Technology» more  IDA 2010»
    Relevant subtask learning by constrained mixture models
    15 years 2 months ago
    Relevant subtask learning by constrained mixture models
    Download  research.ics.tkk.fi
    Jaakko Peltonen, Yusuf Yaslan, Samuel Kaski
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    126
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    FGCN
    2008
    IEEE
    155views Communications» more  FGCN 2008»
    Modeling the Marginal Distribution of Gene Expression with Mixture Models
    15 years 5 months ago
    Modeling the Marginal Distribution of Gene Expression with Mixture Models
    Download  seq.cbrc.jp
    We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
    Edward Wijaya, Hajime Harada, Paul Horton
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