In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Programming models that support code migration have gained prominence, mainly due to a widespread shift from stand-alone to distributed applications. Although appealing in terms o...
Brant Hashii, Scott Malabarba, Raju Pandey, Matt B...
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
The emergence of the Web has made more and more news items available, however only a small subset of these news items are relevant in a decision making process. Therefore decision...
Jethro Borsje, Leonard Levering, Flavius Frasincar