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    NIPS
    2008
    230views Information Technology» more  NIPS 2008»
    Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
    14 years 11 months ago
    Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
    Download  engineering.purdue.edu
    Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
    Guangzhi Cao, Charles A. Bouman
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    SDM
    2003
    SIAM
    184views Data Mining» more  SDM 2003»
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    14 years 11 months ago
    Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
    Download  www-users.cs.umn.edu
    The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
    Levent Ertöz, Michael Steinbach, Vipin Kumar
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    ADC
    2003
    Springer
    123views Database» more  ADC 2003»
    A Distance-Based Packing Method for High Dimensional Data
    15 years 2 months ago
    A Distance-Based Packing Method for High Dimensional Data
    Download  crpit.com
    Minkowski-sum cost model indicates that balanced data partitioning is not beneficial for high dimensional data. Thus we study several unbalanced partitioning methods and propose ...
    Tae-wan Kim, Ki-Joune Li
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    PAKDD
    2009
    ACM
    153views Data Mining» more  PAKDD 2009»
    Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data
    15 years 4 months ago
    Outlier Detection in Axis-Parallel Subspaces of High Dimensional Data
    Download  www.dbs.ifi.lmu.de
    Hans-Peter Kriegel, Peer Kröger, Erich Schube...
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    KDD
    2003
    ACM
    133views Data Mining» more  KDD 2003»
    PROXIMUS: a framework for analyzing very high dimensional discrete-attributed datasets
    15 years 10 months ago
    PROXIMUS: a framework for analyzing very high dimensional discrete-attributed datasets
    Download  vorlon.case.edu
    Ananth Grama, Mehmet Koyutürk
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