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    IJCAI
    2007
    205views Artificial Intelligence» more  IJCAI 2007»
    Locality Sensitive Discriminant Analysis
    13 years 8 months ago
    Locality Sensitive Discriminant Analysis
    Download  www.ijcai.org
    Linear Discriminant Analysis (LDA) is a popular data-analytic tool for studying the class relationship between data points. A major disadvantage of LDA is that it fails to discove...
    Deng Cai, Xiaofei He, Kun Zhou, Jiawei Han, Hujun ...
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    PAKDD
    2007
    ACM
    152views Data Mining» more  PAKDD 2007»
    Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
    14 years 1 months ago
    Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
    Download  www.iipl.fudan.edu.cn
    While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
    Wenxin Yang, Junping Zhang
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    ECCV
    2006
    Springer
    207views Computer Vision» more  ECCV 2006»
    Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
    14 years 9 months ago
    Extending Kernel Fisher Discriminant Analysis with the Weighted Pairwise Chernoff Criterion
    Download  www.cs.ust.hk
    Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
    Guang Dai, Dit-Yan Yeung, Hong Chang
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    JMLR
    2006
    136views more  JMLR 2006»
    Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
    13 years 7 months ago
    Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis
    Download  jmlr.csail.mit.edu
    In this paper we consider a novel Bayesian interpretation of Fisher's discriminant analysis. We relate Rayleigh's coefficient to a noise model that minimises a cost base...
    Tonatiuh Peña Centeno, Neil D. Lawrence
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    PRL
    2010
    209views more  PRL 2010»
    Efficient update of the covariance matrix inverse in iterated linear discriminant analysis
    13 years 2 months ago
    Efficient update of the covariance matrix inverse in iterated linear discriminant analysis
    Download  www.neuroinformatik.ruhr-uni-bochum.de
    For fast classification under real-time constraints, as required in many imagebased pattern recognition applications, linear discriminant functions are a good choice. Linear discr...
    Jan Salmen, Marc Schlipsing, Christian Igel
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