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    ICML
    2008
    IEEE
    129views Machine Learning» more  ICML 2008»
    Fast support vector machine training and classification on graphics processors
    16 years 4 months ago
    Fast support vector machine training and classification on graphics processors
    Download  www.eecs.berkeley.edu
    Bryan C. Catanzaro, Narayanan Sundaram, Kurt Keutz...
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    133
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    ICML
    2003
    IEEE
    157views Machine Learning» more  ICML 2003»
    Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors
    16 years 4 months ago
    Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors
    Download  www.aaai.org
    Dennis DeCoste, Dominic Mazzoni
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    117
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    ML
    2002
    ACM
    180views Machine Learning» more  ML 2002»
    Gene Selection for Cancer Classification using Support Vector Machines
    15 years 3 months ago
    Gene Selection for Cancer Classification using Support Vector Machines
    Download  www.kyb.tuebingen.mpg.de
    Isabelle Guyon, Jason Weston, Stephen Barnhill, Vl...
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    131
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    BMCBI
    2008
    114views more  BMCBI 2008»
    Combining classifiers for improved classification of proteins from sequence or structure
    15 years 3 months ago
    Combining classifiers for improved classification of proteins from sequence or structure
    Download  www.kyb.tuebingen.mpg.de
    Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
    Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
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    157
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    JSS
    2008
    317views more  JSS 2008»
    Predicting defect-prone software modules using support vector machines
    15 years 3 months ago
    Predicting defect-prone software modules using support vector machines
    Download  isi.kfupm.edu.sa
    Effective prediction of defectprone software modules can enable software developers to focus quality assurance activities and allocate effort and resources more efficiently. Supp...
    Karim O. Elish, Mahmoud O. Elish
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