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...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
Image processing techniques and Computer Aided Diagnosis (CAD) systems have proved to be effective for the improvement of radiologists' diagnosis. In this paper an automatic ...
Paola Campadelli, Elena Casiraghi, Giorgio Valenti...
This paper describes an approach for detecting early cognitive loss using medication adherence behavior. We investigate the discriminative power of a comprehensive set of recurren...
Yonghong Huang, Deniz Erdogmus, Zhengdong Lu, Todd...