Many signals of interest are corrupted by faults of an unknown type. We propose an approach that uses Gaussian processes and a general “fault bucket” to capture a priori uncha...
Michael A. Osborne, Roman Garnett, Kevin Swersky, ...
We consider the problem of tag prediction in collaborative tagging systems where users share and annotate resources on the Web. We put forward HAMLET, a novel approach to automatic...
Adriana Budura, Sebastian Michel, Philippe Cudr&ea...
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...
In this paper, we propose a neuro-genetic stock prediction system based on financial correlation between companies. A number of input variables are produced from the relatively h...
We identify and validate from a large corpus constraints from conjunctions on the positive or negative semantic orientation of the conjoined adjectives. A log-linear regression mo...