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    SDM
    2008
    SIAM
    256views Data Mining» more  SDM 2008»
    Graph Mining with Variational Dirichlet Process Mixture Models
    13 years 5 months ago
    Graph Mining with Variational Dirichlet Process Mixture Models
    Download  sato-www.cs.titech.ac.jp
    Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
    Koji Tsuda, Kenichi Kurihara
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    IJCAI
    2007
    253views Artificial Intelligence» more  IJCAI 2007»
    Collapsed Variational Dirichlet Process Mixture Models
    13 years 5 months ago
    Collapsed Variational Dirichlet Process Mixture Models
    Download  www.ics.uci.edu
    Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
    Kenichi Kurihara, Max Welling, Yee Whye Teh
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    KDD
    2007
    ACM
    237views Data Mining» more  KDD 2007»
    Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior
    14 years 4 months ago
    Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior
    Download  www.r.dl.itc.u-tokyo.ac.jp
    Documents, such as those seen on Wikipedia and Folksonomy, have tended to be assigned with multiple topics as a meta-data. Therefore, it is more and more important to analyze a re...
    Issei Sato, Hiroshi Nakagawa
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    JMLR
    2010
    169views more  JMLR 2010»
    Matrix-Variate Dirichlet Process Mixture Models
    12 years 11 months ago
    Matrix-Variate Dirichlet Process Mixture Models
    Download  www.cs.berkeley.edu
    We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
    Zhihua Zhang, Guang Dai, Michael I. Jordan
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    SDM
    2009
    SIAM
    394views Data Mining» more  SDM 2009»
    Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
    14 years 1 months ago
    Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
    Download  www.cs.iastate.edu
    Many real-world applications call for learning predictive relationships from multi-modal data. In particular, in multi-media and web applications, given a dataset of images and th...
    Oksana Yakhnenko, Vasant Honavar
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