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    ALENEX
    2010
    163views Algorithms» more  ALENEX 2010»
    Succinct Trees in Practice
    13 years 8 months ago
    Succinct Trees in Practice
    Download  www.dcc.uchile.cl
    We implement and compare the major current techniques for representing general trees in succinct form. This is important because a general tree of n nodes is usually represented i...
    Diego Arroyuelo, Rodrigo Cánovas, Gonzalo N...
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    APVIS
    2007
    130views Information Technology» more  APVIS 2007»
    A comparison of vertex ordering algorithms for large graph visualization
    13 years 8 months ago
    A comparison of vertex ordering algorithms for large graph visualization
    Download  www.osl.iu.edu
    In this study, we examine the use of graph ordering algorithms for visual analysis of data sets using visual similarity matrices. Visual similarity matrices display the relationsh...
    Christopher Mueller, Benjamin Martin, Andrew Lumsd...
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    IPCO
    2010
    125views Optimization» more  IPCO 2010»
    A Pumping Algorithm for Ergodic Stochastic Mean Payoff Games with Perfect Information
    13 years 8 months ago
    A Pumping Algorithm for Ergodic Stochastic Mean Payoff Games with Perfect Information
    Download  www.mpi-inf.mpg.de
    Abstract. We consider two-person zero-sum stochastic mean payoff games with perfect information, or BWR-games, given by a digraph G = (V = VB VW VR, E), with local rewards r : E R...
    Endre Boros, Khaled M. Elbassioni, Vladimir Gurvic...
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    SDM
    2010
    SIAM
    259views Data Mining» more  SDM 2010»
    Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning
    13 years 8 months ago
    Semi-supervised Bio-named Entity Recognition with Word-Codebook Learning
    Download  paul.rutgers.edu
    We describe a novel semi-supervised method called WordCodebook Learning (WCL), and apply it to the task of bionamed entity recognition (bioNER). Typical bioNER systems can be seen...
    Pavel P. Kuksa, Yanjun Qi
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    NIPS
    2008
    143views Information Technology» more  NIPS 2008»
    Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization
    13 years 8 months ago
    Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization
    Download  www.cs.cmu.edu
    The cluster assumption is exploited by most semi-supervised learning (SSL) methods. However, if the unlabeled data is merely weakly related to the target classes, it becomes quest...
    Liu Yang, Rong Jin, Rahul Sukthankar
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