In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
Lymphangioleiomyomatosis (LAM) is a multisystem disorder associated with proliferation of smooth muscle-like cells, which leads to destruction of lung parenchyma. Subjective gradi...
Jianhua Yao, Nilo Avila, Andrew Dwyer, Angelo M. T...
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...