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    SDM
    2008
    SIAM
    138views Data Mining» more  SDM 2008»
    Clustering from Constraint Graphs
    13 years 11 months ago
    Clustering from Constraint Graphs
    Download  www.cs.cmu.edu
    In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
    Ari Freund, Dan Pelleg, Yossi Richter
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    SDM
    2008
    SIAM
    164views Data Mining» more  SDM 2008»
    Randomizing Social Networks: a Spectrum Preserving Approach
    13 years 11 months ago
    Randomizing Social Networks: a Spectrum Preserving Approach
    Download  coitweb.uncc.edu
    Understanding the general properties of real social networks has gained much attention due to the proliferation of networked data. The nodes in the network are the individuals and...
    Xiaowei Ying, Xintao Wu
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    SDM
    2008
    SIAM
    118views Data Mining» more  SDM 2008»
    Massive-Scale Kernel Discriminant Analysis: Mining for Quasars
    13 years 11 months ago
    Massive-Scale Kernel Discriminant Analysis: Mining for Quasars
    Download  www.cc.gatech.edu
    We describe a fast algorithm for kernel discriminant analysis, empirically demonstrating asymptotic speed-up over the previous best approach. We achieve this with a new pattern of...
    Ryan Riegel, Alexander Gray, Gordon Richards
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    SDM
    2008
    SIAM
    206views Data Mining» more  SDM 2008»
    Latent Variable Mining with Its Applications to Anomalous Behavior Detection
    13 years 11 months ago
    Latent Variable Mining with Its Applications to Anomalous Behavior Detection
    Download  www.ibis.t.u-tokyo.ac.jp
    In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
    Shunsuke Hirose, Kenji Yamanishi
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    SDM
    2008
    SIAM
    177views Data Mining» more  SDM 2008»
    Cluster Ensemble Selection
    13 years 11 months ago
    Cluster Ensemble Selection
    Download  web.engr.oregonstate.edu
    This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
    Xiaoli Z. Fern, Wei Lin
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