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    STOC
    1996
    ACM
    115views Algorithms» more  STOC 1996»
    Minimum Cuts in Near-Linear Time
    15 years 1 months ago
    Minimum Cuts in Near-Linear Time
    Download  www.cs.ust.hk
    We significantly improve known time bounds for solving the minimum cut problem on undirected graphs. We use a "semiduality" between minimum cuts and maximum spanning tree...
    David R. Karger
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    ICDM
    2009
    IEEE
    174views Data Mining» more  ICDM 2009»
    Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
    15 years 4 months ago
    Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
    Download  www.ee.surrey.ac.uk
    —We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
    Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
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    SPEECH
    1998
    171views more  SPEECH 1998»
    Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition
    14 years 9 months ago
    Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition
    Download  www2.ece.jhu.edu
    We present the theory for heteroscedastic discriminant analysis (HDA), a model-based generalization of linear discriminant analysis (LDA) derived in the maximum-likelihood framewo...
    Nagendra Kumar, Andreas G. Andreou
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    BMVC
    2001
    181views Computer Vision» more  BMVC 2001»
    Recognising Trajectories of Facial Identities Using Kernel Discriminant Analysis
    15 years 4 days ago
    Recognising Trajectories of Facial Identities Using Kernel Discriminant Analysis
    Download  www.bmva.ac.uk
    We present a comprehensive approach to address three challenging problems in face recognition: modelling faces across multi-views, extracting the non-linear discriminating feature...
    Yongmin Li, Shaogang Gong, Heather M. Liddell
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    ICCV
    2009
    IEEE
    602views Computer Vision» more  ICCV 2009»
    Max-Margin Additive Classifiers for Detection
    16 years 2 months ago
    Max-Margin Additive Classifiers for Detection
    Download  www.cs.berkeley.edu
    We present methods for training high quality object detectors very quickly. The core contribution is a pair of fast training algorithms for piece-wise linear classifiers, which ...
    Subhransu Maji, Alexander C. Berg
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