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    SAC
    2008
    ACM
    153views Applied Computing» more  SAC 2008»
    Frequent pattern mining for kernel trace data
    13 years 7 months ago
    Frequent pattern mining for kernel trace data
    Download  www.mathcs.emory.edu
    Operating systems engineers have developed tracing tools that log details about process execution at the kernel level. These tools make it easier to understand the actual executio...
    Christopher LaRosa, Li Xiong, Ken Mandelberg
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    KDD
    2004
    ACM
    181views Data Mining» more  KDD 2004»
    Column-generation boosting methods for mixture of kernels
    14 years 8 months ago
    Column-generation boosting methods for mixture of kernels
    Download  stat.rutgers.edu
    We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
    Jinbo Bi, Tong Zhang, Kristin P. Bennett
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    CCS
    2009
    ACM
    158views Security Privacy» more  CCS 2009»
    Countering kernel rootkits with lightweight hook protection
    14 years 2 months ago
    Countering kernel rootkits with lightweight hook protection
    Download  discovery.csc.ncsu.edu
    Kernel rootkits have posed serious security threats due to their stealthy manner. To hide their presence and activities, many rootkits hijack control flows by modifying control d...
    Zhi Wang, Xuxian Jiang, Weidong Cui, Peng Ning
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    RIVF
    2008
    172views Internet Technology» more  RIVF 2008»
    Simple but effective methods for combining kernels in computational biology
    13 years 9 months ago
    Simple but effective methods for combining kernels in computational biology
    Download  www.jaist.ac.jp
    Complex biological data generated from various experiments are stored in diverse data types in multiple datasets. By appropriately representing each biological dataset as a kernel ...
    Hiroaki Tanabe, Tu Bao Ho, Canh Hao Nguyen, Saori ...
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    ADCM
    2006
    74views more  ADCM 2006»
    Linearly constrained reconstruction of functions by kernels with applications to machine learning
    13 years 7 months ago
    Linearly constrained reconstruction of functions by kernels with applications to machine learning
    Download  num.math.uni-goettingen.de
    This paper investigates the approximation of multivariate functions from data via linear combinations of translates of a positive definite kernel from a reproducing kernel Hilbert...
    Robert Schaback, J. Werner
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