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    SPAA
    1993
    ACM
    134views Distributed And Parallel Com...» more  SPAA 1993»
    On Gazit and Miller's Parallel Algorithm for Planar Separators: Achieving Greater Efficiency Through Random Sampling
    13 years 10 months ago
    On Gazit and Miller's Parallel Algorithm for Planar Separators: Achieving Greater Efficiency Through Random Sampling
    Download  www.cs.brown.edu
    We show how to obtain a work-efficient parallel algorithm for finding a planar separator. The algorithm requires O(rz’ ) time for any given positive constant e.
    Philip N. Klein
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    ICDCS
    2005
    IEEE
    103views Distributed And Parallel Com...» more  ICDCS 2005»
    An In-Depth, Analytical Study of Sampling Techniques for Self-Similar Internet Traffic
    13 years 11 months ago
    An In-Depth, Analytical Study of Sampling Techniques for Self-Similar Internet Traffic
    Download  www.cecs.uci.edu
    Guanghui He, Jennifer C. Hou
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    IPPS
    1998
    IEEE
    87views Distributed And Parallel Com...» more  IPPS 1998»
    Parallel Randomized Techniques for Some Fundamental Geometric Problems: A Survey
    13 years 9 months ago
    Parallel Randomized Techniques for Some Fundamental Geometric Problems: A Survey
    Download  ipdps.cc.gatech.edu
    Suneeta Ramaswami
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    PODC
    2006
    ACM
    90views Distributed And Parallel Com...» more  PODC 2006»
    Peer counting and sampling in overlay networks: random walk methods
    14 years 1 days ago
    Peer counting and sampling in overlay networks: random walk methods
    Download  www.irisa.fr
    Laurent Massoulié, Erwan Le Merrer, Anne-Ma...
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    ECCV
    2008
    Springer
    168views Computer Vision» more  ECCV 2008»
    A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus
    14 years 8 months ago
    A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus
    Download  gamma.cs.unc.edu
    The Random Sample Consensus (RANSAC) algorithm is a popular tool for robust estimation problems in computer vision, primarily due to its ability to tolerate a tremendous fraction o...
    Rahul Raguram, Jan-Michael Frahm, Marc Pollefeys
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