657 search results - page 3 / 132 » Scaling-Up Support Vector Machines Using Boosting Algorithm |
PAKDD
2005
ACM
13 years 10 months ago
2005
ACM
Abstract. Hard margin support vector machines (HM-SVMs) have a risk of getting overfitting in the presence of the noise. Soft margin SVMs deal with this
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
TNN
2008
13 years 5 months ago
2008
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
FGR
2006
IEEE
13 years 11 months ago
2006
IEEE
We examined the effectiveness of using Haar features and the Adaboost boosting algorithm for FACS action unit (AU) recognition. We evaluated both recognition accuracy and processi...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...