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https://dl.acm.org/doi/10.1145/1989323.1989398
Exact indexing for support vector machines. Pages 709–720. Previous Chapter Next Chapter. ABSTRACT. SVM (Support Vector Machine) is a well-established machine learning methodology popularly used for classification, regression, and ranking. Recently SVM has been actively researched for rank learning and applied to various applications ...
https://www.sciencedirect.com/science/article/pii/S0020025513006592
A preliminary version of the paper, “Exact Indexing for Support Vector Machines”, appeared in Proc. ACM SIGMOD 2011. However, this submission has substantially extended the previous paper and contains new and major-value added technical contribution in comparison with the conference publication. ☆☆Cited by: 3
https://dl.acm.org/citation.cfm?id=1989398
SVM (Support Vector Machine) is a well-established machine learning methodology popularly used for classification, regression, and ranking. Recently SVM has been actively researched for rank learning and applied to various applications including search engines or relevance feedback systems.Cited by: 10
https://www.researchgate.net/publication/221214704_IKernel_Exact_indexing_for_support_vector_machines
Support Vector Machines (SVMs) have been adopted by many data-mining and information-retrieval applications for learning a mining or query concept, and then retrieving the "top-k" best matches to ...
https://sites.google.com/site/postechdm/research/implementation/iKernel
This code is publicly available to facilitate research and education in the related areas of data mining and machine learning. If you publish material based on this code, please refer to the source as follows, to help others to obtain the same code and reproduce your experiments.
https://www.researchgate.net/publication/3297557_KDX_An_Indexer_for_Support_Vector_Machines
Support Vector Machines (SVMs) have been adopted by many data-mining and information-retrieval applications for learning a mining or query concept, and then retrieving the "top-k" best matches to ...
https://epubs.siam.org/doi/pdf/10.1137/1.9781611972757.29
Exploiting Geometry for Support Vector Machine Indexing∗ Navneet Panda† Edward Y. Chang‡ Abstract Support Vector Machines (SVMs) have been adopted by many data-mining and information-retrieval applications for learning a mining or query concept, and then retrieving the “top-k” best matches to the concept. However, when
https://en.wikipedia.org/wiki/Support_vector_machine
The soft-margin support vector machine described above is an example of an empirical risk minimization (ERM) algorithm for the hinge loss. Seen this way, support vector machines belong to a natural class of algorithms for statistical inference, and many of its unique features are due to …
https://sites.google.com/site/postechdm/research/publication/International-journal
iKernel: Exact Indexing for Support Vector Machines Information Sciences (SCI) 2014.02 20 J Kim, WS Han, J Oh, S Kim, H Yu Processing Time-Dependent Shortest Path Queries Without Pre-computed Speed Information on Road Networks Information Sciences (SCI) 2014.01 19 S Kim, L Sael, H Yu
https://www.mathworks.com/help/stats/support-vector-machines-for-binary-classification.html
Support Vector Machines for Binary Classification Understanding Support Vector Machines. Separable Data. Nonseparable Data. Nonlinear Transformation with Kernels. Separable Data. You can use a support vector machine (SVM) when your data has exactly two classes.
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