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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 ...
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.66.1609
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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 the dataset is large, naively scanning the entire dataset to find the top matches is not ...
https://www.slideserve.com/lschuller/kdx-an-indexer-for-support-vector-machines-powerpoint-ppt-presentation
KDX: An indexer for support vector machines. Advisor : Dr. Hsu Presenter : Yu-San Hsieh Author : Navneet Panda, Edward Y. Chang. 2006. TKDE.748-763. Outline ...
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000001626230
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 the data set is large, naively scanning the entire data set to …
https://core.ac.uk/display/24461713
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 the dataset is large, naively scanning …Author: Edward Y. Chang
https://dl.acm.org/doi/10.1145/1989323.1989398
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. ... Kdx: An indexer for support vector machines. IEEE ...
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
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.215.4884
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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 the dataset is large, naively scanning the entire dataset to find the top matches is not ...
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: 11
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.2345
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): 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 the dataset is large, naively scanning the entire dataset to find the top matches is not ...
http://infolab.stanford.edu/~echang/NSF-IIS-0535085.html
Six scalable algorithms developed by this project are 1) PSVM, 2) CCF, 3) PFP, 4) Parallel Spectral Clustering, 5) PLDA, and 6) KDX. 1) PSVM: Support Vector Machines suffer from a widely recognized scalability problem in both memory use and computational time.
https://www.slideserve.com/lschuller/kdx-an-indexer-for-support-vector-machines-powerpoint-ppt-presentation
KDX: An indexer for support vector machines. Advisor : Dr. Hsu Presenter : Yu-San Hsieh Author : Navneet Panda, Edward Y. Chang. 2006. TKDE.748-763. Outline ...
https://www.researchgate.net/publication/2331557_Classification_of_News_Stories_Using_Support_Vector_Machines
Support vector machines (Vapnik, 1995 ) are a computational method for performing simultaneous feature space reduction and binary classification based on Vapnik's statistical learning theory.
https://www.researchgate.net/publication/264997991_Canonical_duality_solution_for_alternating_support_vector_machine
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://www.aimsciences.org/article/doi/10.3934/jimo.2012.8.611
Support vector machine (SVM) is one of the most popular machine learning methods and is educed from a binary data classification problem. In this paper, the canonical duality theory is used to solve the normal model of SVM. Several examples are illustrated to show that the exact solution can be obtained after the canonical duality problem being solved.
https://www.sciencedirect.com/science/article/pii/S0020025513006592
iKernel: Exact indexing for support vector machines ... KDX , and the other is a metric-based index, M-tree , which is modified to support SVM indexing. Our experiments were done on a linux machine with two quadcore CPUs (2.27 GHz) and 24G memory. ... E. ChangKdx: an indexer for support vector machines. IEEE Transactions on Knowledge and Data ...
https://www.sciencedirect.com/science/article/pii/S0895717712002658
It is a very interesting topic to forecast the movement direction of financial time series by machine learning methods. Among these machine learning methods, support vector machine (SVM) is the most effective and intelligent one. A new learning model is presented in this paper, called the polynomial smooth support vector machine (PSSVM).
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 ...
http://www.shmula.com/wp-content/uploads/2011/05/navneet-panda-google-pandaresume.pdf
• KDX: An Indexer for Support Vector Machines, Navneet Panda and Edward Y. Chang (Transactions of Knowledge and Data Engineering, TKDE June 2006) • Active Learning in Very Large Databases, Navneet Panda, Kingshy Goh and Edward Y. Chang (Journal of Multimedia Tools and Applications Special Issue on Computer Vision Meets Databases)
https://dl.acm.org/citation.cfm?id=299100
Navneet Panda , Edward Y. Chang, KDX: An Indexer for Support Vector Machines, IEEE Transactions on Knowledge and Data Engineering, v.18 n.6, p.748-763, June 2006 ... Wavelet time-frequency analysis and least squares support vector machines for the identification of voice disorders, Computers in Biology and Medicine, v.37 n.4, p.571-578, April, 2007
https://dl.acm.org/citation.cfm?id=2326469
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https://doi.acm.org/10.1145/500141.500159
Relevance feedback is often a critical component when designing image databases. With these databases it is difficult to specify queries directly and explicitly. Relevance feedbac
http://core.ac.uk/display/21737767
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 the dataset is large, naively scanning …
https://dl.acm.org/citation.cfm?id=658272
Manabu Sassano, An empirical study of active learning with support vector machines for Japanese word segmentation, Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, July 07-12, 2002, Philadelphia, Pennsylvania ... KDX: An Indexer for Support Vector Machines, IEEE Transactions on Knowledge and Data Engineering ...
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