In recent years, Support Vector Machines (SVMs) were successfully applied to a wide range of applications. Their good performance is achieved by an implicit non-linear transformat...
David Martens, Bart Baesens, Tony Van Gestel, Jan ...
Several solutions have been proposed to exploit the availability of heterogeneous sources of biomolecular data for gene function prediction, but few attention has been dedicated t...
An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. T...
The scores returned by support vector machines are often used as a confidence measures in the classification of new examples. However, there is no theoretical argument sustaining ...
Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...