217 search results - page 16 / 44 » Training Hard-Margin Support Vector Machines Using Greedy St... |
AHS
2007
IEEE
14 years 2 months ago
2007
IEEE
Machine Learning algorithms allow to create highly adaptable systems, since their functionality only depends on the features of the inputs and the coefficients found during the tr...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Support Vector Machines (SVMs) suffer from an O(n2 ) training cost, where n denotes the number of training instances. In this paper, we propose an algorithm to select boundary ins...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
In this paper, we extend the recently proposed Core Vector Machine algorithm to the regression setting by generalizing the underlying minimum enclosing ball problem. The resultant...
COLT
2005
Springer
14 years 1 months ago
2005
Springer
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
AIME
2009
Springer
13 years 5 months ago
2009
Springer
Lung cancer represents the most deadly type of malignancy. In this work we propose a machine learning approach to segmenting lung tumours in Positron Emission Tomography (PET) scan...