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    JMLR
    2006
    148views more  JMLR 2006»
    Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
    13 years 7 months ago
    Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
    Download  jmlr.csail.mit.edu
    Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
    Jieping Ye, Tao Xiong
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    EMNLP
    2010
    185views Natural Language Processing» more  EMNLP 2010»
    A Fast Decoder for Joint Word Segmentation and POS-Tagging Using a Single Discriminative Model
    13 years 5 months ago
    A Fast Decoder for Joint Word Segmentation and POS-Tagging Using a Single Discriminative Model
    Download  www.cse.ohio-state.edu
    We show that the standard beam-search algorithm can be used as an efficient decoder for the global linear model of Zhang and Clark (2008) for joint word segmentation and POS-taggi...
    Yue Zhang 0004, Stephen Clark
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    ICDAR
    2009
    IEEE
    179views Document Analysis» more  ICDAR 2009»
    A Novel Rejection Measurement in Handwritten Numeral Recognition Based on Linear Discriminant Analysis
    14 years 2 months ago
    A Novel Rejection Measurement in Handwritten Numeral Recognition Based on Linear Discriminant Analysis
    Download  www.cvc.uab.es
    Chun Lei He, Louisa Lam, Ching Y. Suen
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    TKDE
    2008
    152views more  TKDE 2008»
    SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
    13 years 7 months ago
    SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis
    Download  www.cs.uiuc.edu
    Linear Discriminant Analysis (LDA) has been a popular method for extracting features that preserves class separability. The projection functions of LDA are commonly obtained by max...
    Deng Cai, Xiaofei He, Jiawei Han
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    PAMI
    2008
    162views more  PAMI 2008»
    Dimensionality Reduction of Clustered Data Sets
    13 years 7 months ago
    Dimensionality Reduction of Clustered Data Sets
    Download  eprints.pascal-network.org
    We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
    Guido Sanguinetti
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