In this paper we apply boosting to learn complex non-linear local visual feature representations, drawing inspiration from its successful application to visual object detection. The main goal of local feature descriptors is to distinctively represent a salient image region while remaining invariant to viewpoint and illumination changes. This representation can be improved using machine learning...

Chromatin-remodeling proteins have a profound role in the transcriptional regulation of gene expression during development. Here, we have shown that the chromodomain-containing protein Hat-trick is predominantly expressed within the oocyte nucleus, specifically within the heterochromatinized karyosome, and that a mild expression is observed in follicle cells. Colocalization of Hat-trick with He...

The Self Organizing Map is a nonlinear projection technique that allows to visualize the underlying structure of high dimensional data. However, the original algorithm relies on the use of Euclidean distances which often becomes a serious drawback for a number of real problems. In this paper, we present a new kernel version of the SOM algorithm that incorporates non-Euclidean dissimilarities ke...

This paper present a principled SVM based speaker verification system. We propose a new framework and a new sequence kernel that can make use of any Mercer kernel at the frame level. An extension of the sequence kernel based on the Max operator is also proposed. The new system is compared to state-of-the-art GMM and other SVM based systems found in the literature on the Banca and Polyvar databa...

MOTIVATION The correlation among fragment ions in a tandem mass spectrum is crucial in reducing stochastic mismatches for peptide identification by database searching. Until now, an efficient scoring algorithm that considers the correlative information in a tunable and comprehensive manner has been lacking. RESULTS This paper provides a promising approach to utilizing the correlative informat...