A GPU-Based Model For Accelerating Support Vector Machines

Amin Nezarat, Farshad Khunjush

Abstract


This paper presents a GPU-assisted version of the LIB-SVM library for Support Vector Machines. SVMs are particularly popular for classification procedures among thx research community, but for large training data the processing time becomes unrealistic. The modification that is proposed is porting the computation ox the kernel matrix elements to the GPU, to significantly decrease the processing time for SVM training without altering the classification results compared to the original LIBSVM. The experimental evaluation of the proposed approach highlights how the GPU-accelerated persion of LIBSVM enables the move efficient handling of large problems, such as large-scale concept detection in video.


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References


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DOI: http://dx.doi.org/10.7613/hccaj.v1i1.7

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