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    CIBCB
    2008
    IEEE
    158views Computational Biology» more  CIBCB 2008»
    Very large scale ReliefF for genome-wide association analysis
    14 years 2 months ago
    Very large scale ReliefF for genome-wide association analysis
    Download  www.cs.uvm.edu
    — The genetic causes of many monogenic diseases have already been discovered. However, most common diseases are actually the result of complex nonlinear interactions between mult...
    Margaret J. Eppstein, Paul Haake
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    SDM
    2009
    SIAM
    205views Data Mining» more  SDM 2009»
    Identifying Information-Rich Subspace Trends in High-Dimensional Data.
    14 years 4 months ago
    Identifying Information-Rich Subspace Trends in High-Dimensional Data.
    Download  www.siam.org
    Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
    Chandan K. Reddy, Snehal Pokharkar
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    NN
    2006
    Springer
    113views Neural Networks» more  NN 2006»
    Large-scale data exploration with the hierarchically growing hyperbolic SOM
    13 years 7 months ago
    Large-scale data exploration with the hierarchically growing hyperbolic SOM
    Download  ani.www.techfak.uni-bielefeld.de
    We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2 SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that al...
    Jörg Ontrup, Helge Ritter
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    SDM
    2004
    SIAM
    225views Data Mining» more  SDM 2004»
    Active Semi-Supervision for Pairwise Constrained Clustering
    13 years 9 months ago
    Active Semi-Supervision for Pairwise Constrained Clustering
    Download  www.cs.utexas.edu
    Semi-supervised clustering uses a small amount of supervised data to aid unsupervised learning. One typical approach specifies a limited number of must-link and cannotlink constra...
    Sugato Basu, Arindam Banerjee, Raymond J. Mooney
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    WSDM
    2012
    ACM
    304views Data Mining» more  WSDM 2012»
    Beyond co-occurrence: discovering and visualizing tag relationships from geo-spatial and temporal similarities
    12 years 3 months ago
    Beyond co-occurrence: discovering and visualizing tag relationships from geo-spatial and temporal similarities
    Download  www.cs.indiana.edu
    Studying relationships between keyword tags on social sharing websites has become a popular topic of research, both to improve tag suggestion systems and to discover connections b...
    Haipeng Zhang, Mohammed Korayem, Erkang You, David...
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