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    SDM
    2004
    SIAM
    162views Data Mining» more  SDM 2004»
    Subspace Clustering of High Dimensional Data
    13 years 8 months ago
    Subspace Clustering of High Dimensional Data
    Download  alumni.cs.ucr.edu
    Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
    Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
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    SUTC
    2008
    IEEE
    138views Sensor Networks» more  SUTC 2008»
    Effective Feature Space Reduction with Imbalanced Data for Semantic Concept Detection
    14 years 1 months ago
    Effective Feature Space Reduction with Imbalanced Data for Semantic Concept Detection
    Download  users.cis.fiu.edu
    Semantic understanding of multimedia content has become a very popular research topic in recent years. Semantic concept detection algorithms face many challenges such as the seman...
    Lin Lin, Guy Ravitz, Mei-Ling Shyu, Shu-Ching Chen
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    ESANN
    2007
    135views Neural Networks» more  ESANN 2007»
    Kernel PCA based clustering for inducing features in text categorization
    13 years 8 months ago
    Kernel PCA based clustering for inducing features in text categorization
    Download  www.dice.ucl.ac.be
    We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
    Zsolt Minier, Lehel Csató
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    FGR
    2006
    IEEE
    162views Biometrics» more  FGR 2006»
    Hierarchical Ensemble of Gabor Fisher Classifier for Face Recognition
    13 years 10 months ago
    Hierarchical Ensemble of Gabor Fisher Classifier for Face Recognition
    Download  www.jdl.ac.cn
    Gabor feature has been widely recognized as one of the best representations for face recognition. However, traditionally, it has to be reduced in dimension due to curse of dimensi...
    Yu Su, Shiguang Shan, Xilin Chen, Wen Gao
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    JMM2
    2006
    110views more  JMM2 2006»
    Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition
    13 years 6 months ago
    Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition
    Download  www.academypublisher.com
    We propose a technique for gait recognition from motion capture data based on two successive stages of principal component analysis (PCA) on kinematic data. The first stage of PCA ...
    Sandhitsu R. Das, Robert C. Wilson, Maciej T. Laza...
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