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    KDD
    2004
    ACM
    139views Data Mining» more  KDD 2004»
    Learning a complex metabolomic dataset using random forests and support vector machines
    14 years 7 months ago
    Learning a complex metabolomic dataset using random forests and support vector machines
    Download  math.uc.edu
    Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
    Young Truong, Xiaodong Lin, Chris Beecher
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    TNN
    2010
    143views Management» more  TNN 2010»
    Using unsupervised analysis to constrain generalization bounds for support vector classifiers
    13 years 2 months ago
    Using unsupervised analysis to constrain generalization bounds for support vector classifiers
    Download  www.smartlab.dibe.unige.it
    Abstract--A crucial issue in designing learning machines is to select the correct model parameters. When the number of available samples is small, theoretical sample-based generali...
    Sergio Decherchi, Sandro Ridella, Rodolfo Zunino, ...
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    ICML
    2005
    IEEE
    160views Machine Learning» more  ICML 2005»
    Building Sparse Large Margin Classifiers
    14 years 8 months ago
    Building Sparse Large Margin Classifiers
    Download  www.kyb.mpg.de
    This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
    Bernhard Schölkopf, Gökhan H. Bakir, Min...
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    CORR
    2008
    Springer
    113views Education» more  CORR 2008»
    Robustness, Risk, and Regularization in Support Vector Machines
    13 years 7 months ago
    Robustness, Risk, and Regularization in Support Vector Machines
    Download  users.ece.utexas.edu
    We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
    Huan Xu, Shie Mannor, Constantine Caramanis
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    BMCBI
    2008
    170views more  BMCBI 2008»
    A genetic approach for building different alphabets for peptide and protein classification
    13 years 7 months ago
    A genetic approach for building different alphabets for peptide and protein classification
    Download  www.biomedcentral.com
    Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
    Loris Nanni, Alessandra Lumini
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