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    IJCNN
    2008
    IEEE
    93views Neural Networks» more  IJCNN 2008»
    Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications
    15 years 4 months ago
    Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications
    Download  www.smartlab.dibe.unige.it
    — In this work we show that a metaheuristic, the Variable Neighborhood Search (VNS), can be effectively used in order to improve the performance of the hardware–friendly versio...
    Enrique Alba, Davide Anguita, Alessandro Ghio, San...
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    WINE
    2005
    Springer
    268views Economy» more  WINE 2005»
    Mining Stock Market Tendency Using GA-Based Support Vector Machines
    15 years 3 months ago
    Mining Stock Market Tendency Using GA-Based Support Vector Machines
    Download  www.svms.org
    In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
    Lean Yu, Shouyang Wang, Kin Keung Lai
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    IFIP12
    2007
    164views Information Technology» more  IFIP12 2007»
    Patient Fall Detection using Support Vector Machines
    14 years 11 months ago
    Patient Fall Detection using Support Vector Machines
    Download  www.ait.gr
    This paper presents a novel implementation of a patient fall detection system that may be used for patient activity recognition and emergency treatment. Sensors equipped with accel...
    Charalampos Doukas, Ilias Maglogiannis, Philippos ...
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    NAACL
    2007
    142views Computational Linguistics» more  NAACL 2007»
    Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
    14 years 11 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
    14 years 11 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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