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    » Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
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    SDM
    2010
    SIAM
    151views Data Mining» more  SDM 2010»
    Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
    13 years 6 months ago
    Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs
    Download  www.cc.gatech.edu
    The high computational cost of nonlinear support vector machines has limited their usability for large-scale problems. We propose two novel stochastic algorithms to tackle this pr...
    Hua Ouyang, Alexander Gray
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    SDM
    2011
    SIAM
    232views Data Mining» more  SDM 2011»
    A Sequential Dual Method for Structural SVMs
    12 years 7 months ago
    A Sequential Dual Method for Structural SVMs
    Download  www.keerthis.com
    In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to computationa...
    Shirish Krishnaj Shevade, Balamurugan P., S. Sunda...
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    ICRA
    2006
    IEEE
    102views Robotics» more  ICRA 2006»
    Fast Iterative Alignment of Pose Graphs with Poor Initial Estimates
    13 years 11 months ago
    Fast Iterative Alignment of Pose Graphs with Poor Initial Estimates
    Download  rvsn.csail.mit.edu
    — A robot exploring an environment can estimate its own motion and the relative positions of features in the environment. Simultaneous Localization and Mapping (SLAM) algorithms ...
    Edwin Olson, John J. Leonard, Seth J. Teller
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    ICPR
    2008
    IEEE
    195views Computer Vision» more  ICPR 2008»
    Kernel Bisecting k-means clustering for SVM training sample reduction
    13 years 11 months ago
    Kernel Bisecting k-means clustering for SVM training sample reduction
    Download  figment.cse.usf.edu
    This paper presents a new algorithm named Kernel Bisecting k-means and Sample Removal (KBK-SR) as a sampling preprocessing for SVM training to improve the scalability. The novel c...
    Xiao-Zhang Liu, Guo-Can Feng
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    AUTOMATICA
    2011
    241views Artificial Intelligence» more  AUTOMATICA 2011»
    Distributed dynamic programming for discrete-time stochastic control, and idempotent algorithms
    12 years 12 months ago
    Distributed dynamic programming for discrete-time stochastic control, and idempotent algorithms
    Download  maeresearch.ucsd.edu
    Previously, idempotent methods have been found to be extremely fast for solution of dynamic programming equations associated with deterministic control problems. The original meth...
    William M. McEneaney
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