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    NAACL
    2007
    142views Computational Linguistics» more  NAACL 2007»
    Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
    13 years 9 months ago
    Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
    Download  www.cs.utexas.edu
    We present a method for utilizing unannotated sentences to improve a semantic parser which maps natural language (NL) sentences into their formal meaning representations (MRs). Gi...
    Rohit J. Kate, Raymond J. Mooney
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    ICONIP
    2004
    149views Information Technology» more  ICONIP 2004»
    Content-Based Video Classification Using Support Vector Machines
    13 years 9 months ago
    Content-Based Video Classification Using Support Vector Machines
    Download  www.columbia.edu
    Abstract. In this paper, we investigate the problem of video classification into predefined genre. The approach adopted is based on spatial and temporal descriptors derived from sh...
    Vakkalanka Suresh, C. Krishna Mohan, R. Kumara Swa...
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    NIPS
    1998
    138views Information Technology» more  NIPS 1998»
    Dynamically Adapting Kernels in Support Vector Machines
    13 years 9 months ago
    Dynamically Adapting Kernels in Support Vector Machines
    Download  www.support-vector.net
    The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
    Nello Cristianini, Colin Campbell, John Shawe-Tayl...
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    NIPS
    2000
    148views Information Technology» more  NIPS 2000»
    Active Support Vector Machine Classification
    13 years 9 months ago
    Active Support Vector Machine Classification
    Download  www.iipl.fudan.edu.cn
    An active set strategy is applied to the dual of a simple reformulation of the standard quadratic program of a linear support vector machine. This application generates a fast new...
    Olvi L. Mangasarian, David R. Musicant
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    PAMI
    2006
    128views more  PAMI 2006»
    Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
    13 years 7 months ago
    Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues
    Download  people.ee.duke.edu
    A new approach to support vector machine (SVM) classification is proposed wherein each of two data sets are proximal to one of two distinct planes that are not parallel to each oth...
    Olvi L. Mangasarian, Edward W. Wild
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