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» Training Data Selection for Support Vector Machines
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TNN
2010
159views Management» more  TNN 2010»
14 years 7 months ago
Multiple incremental decremental learning of support vector machines
We propose a multiple incremental decremental algorithm of Support Vector Machine (SVM). Conventional single incremental decremental SVM can update the trained model efficiently w...
Masayuki Karasuyama, Ichiro Takeuchi
105
Voted
ICPR
2006
IEEE
16 years 1 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
111
Voted
ICPR
2002
IEEE
16 years 1 months ago
Incorporating Conditional Independence Assumption with Support Vector Machines to Enhance Handwritten Character Segmentation Per
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Manolis Maragoudakis, Ergina Kavallieratou, Nikos ...
ESANN
2008
15 years 1 months ago
Comparison of sparse least squares support vector regressors trained in primal and dual
In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this p...
Shigeo Abe
98
Voted
IGARSS
2010
14 years 10 months ago
Support vector machines regression for estimation of forest parameters from airborne laser scanning data
Estimation of forest stand parameters from airborne laser scanning data relies on the selection of laser metrics sets and numerous field plots for model calibration. In mountainou...
Jean-Matthieu Monnet, Frédéric Berge...