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» Training Invariant Support Vector Machines
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CVPR
2004
IEEE
15 years 12 months ago
Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter...
Fu Jie Huang, Léon Bottou, Yann LeCun
ICPR
2004
IEEE
15 years 11 months ago
Training of Classifiers Using Virtual Samples Only
This paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. Two classifiers, a support vector machine and a polynomial c...
Annika Kuhl, Lars Krüger, Christian Wöhl...
BMCBI
2007
127views more  BMCBI 2007»
14 years 10 months ago
Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines
Background: Human genetic variations primarily result from single nucleotide polymorphisms (SNPs) that occur approximately every 1000 bases in the overall human population. The no...
Jian Tian, Ningfeng Wu, Xuexia Guo, Jun Guo, Juhua...
NCA
2008
IEEE
14 years 9 months ago
Polynomial kernel adaptation and extensions to the SVM classifier learning
Three extensions to the Kernel-AdaTron training algorithm for Support Vector Machine classifier learning are presented. These extensions allow the trained classifier to adhere more...
Ramy Saad, Saman K. Halgamuge, Jason Li
IJCNN
2006
IEEE
15 years 3 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho