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    KDD
    2010
    ACM
    274views Data Mining» more  KDD 2010»
    Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
    13 years 11 months ago
    Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
    Download  www.cs.cmu.edu
    Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
    Jun Zhu, Ni Lao, Eric P. Xing
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    ICANN
    2007
    Springer
    111views Neural Networks» more  ICANN 2007»
    Classifying EEG Data into Different Memory Loads Across Subjects
    13 years 11 months ago
    Classifying EEG Data into Different Memory Loads Across Subjects
    Download  www.physics.brown.edu
    Abstract. In this paper we consider the question of whether it is possible to classify n-back EEG data into different memory loads across subjects. To capture relevant information ...
    Liang Wu, Predrag Neskovic
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    CEC
    2007
    IEEE
    195views Artificial Intelligence» more  CEC 2007»
    Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
    13 years 11 months ago
    Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms
    Download  www2.lifl.fr
    In this work we compare the use of a Particle Swarm Optimization (PSO) and a Genetic Algorithm (GA) (both augmented with Support Vector Machines SVM) for the classification of high...
    Enrique Alba, José García-Nieto, Lae...
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    BIOINFORMATICS
    2006
    92views more  BIOINFORMATICS 2006»
    What should be expected from feature selection in small-sample settings
    13 years 7 months ago
    What should be expected from feature selection in small-sample settings
    Download  gsp.tamu.edu
    Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
    Chao Sima, Edward R. Dougherty
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    SDM
    2008
    SIAM
    256views Data Mining» more  SDM 2008»
    Graph Mining with Variational Dirichlet Process Mixture Models
    13 years 9 months ago
    Graph Mining with Variational Dirichlet Process Mixture Models
    Download  sato-www.cs.titech.ac.jp
    Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
    Koji Tsuda, Kenichi Kurihara
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