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» Co-Tracking Using Semi-Supervised Support Vector Machines
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143
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ISBI
2008
IEEE
15 years 9 months ago
Support vector driven Markov random fields towards DTI segmentation of the human skeletal muscle
In this paper we propose a classification-based method towards the segmentation of diffusion tensor images. We use Support Vector Machines to classify diffusion tensors and we ex...
Radhouène Neji, Gilles Fleury, Jean Francoi...
126
Voted
DIS
2005
Springer
15 years 8 months ago
Support Vector Inductive Logic Programming
Abstract. In this paper we explore a topic which is at the intersection of two areas of Machine Learning: namely Support Vector Machines (SVMs) and Inductive Logic Programming (ILP...
Stephen Muggleton, Huma Lodhi, Ata Amini, Michael ...
NIPS
2000
15 years 4 months ago
Regularized Winnow Methods
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
Tong Zhang
SAC
2005
ACM
15 years 8 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra
IJON
2006
104views more  IJON 2006»
15 years 2 months ago
Kernel methods and the exponential family
The success of Support Vector Machine (SVM) gave rise to the development of a new class of theoretically elegant learning machines which use a central concept of kernels and the a...
Stéphane Canu, Alexander J. Smola