Abstract. Computational analysis of mass spectrometric (MS) proteomic data from sera is of potential relevance for diagnosis, prognosis, choice of therapy, and study of disease act...
Elena Marchiori, Connie R. Jimenez, Mikkel West-Ni...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
This paper extends our previous work on feature transformationbased support vector machines for speaker recognition by proposing a joint MAP adaptation of feature transformation (...