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    » On Relevant Dimensions in Kernel Feature Spaces
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    ALT
    2004
    Springer
    112views Machine Learning» more  ALT 2004»
    On Kernels, Margins, and Low-Dimensional Mappings
    14 years 4 months ago
    On Kernels, Margins, and Low-Dimensional Mappings
    Download  www.cs.cmu.edu
    Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
    Maria-Florina Balcan, Avrim Blum, Santosh Vempala
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    VIP
    2003
    188views Information Technology» more  VIP 2003»
    Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces
    13 years 8 months ago
    Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces
    Download  crpit.com
    The Continuously Adaptive Mean Shift Algorithm (CamShift) is an adaptation of the Mean Shift algorithm for object tracking that is intended as a step towards head and face trackin...
    John G. Allen, Richard Y. D. Xu, Jesse S. Jin
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    ICDAR
    2009
    IEEE
    219views Document Analysis» more  ICDAR 2009»
    Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization
    13 years 5 months ago
    Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization
    Download  www.cvc.uab.es
    This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
    Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang
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    SDM
    2009
    SIAM
    161views Data Mining» more  SDM 2009»
    Feature Weighted SVMs Using Receiver Operating Characteristics.
    14 years 4 months ago
    Feature Weighted SVMs Using Receiver Operating Characteristics.
    Download  www.siam.org
    Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
    Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
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    NIPS
    2003
    93views Information Technology» more  NIPS 2003»
    Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA
    13 years 8 months ago
    Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA
    Download  books.nips.cc
    We derive the limiting form of the eigenvalue spectrum for sample covariance matrices produced from non-isotropic data. For the analysis of standard PCA we study the case where th...
    David C. Hoyle, Magnus Rattray
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