Graph Languages1 emerged during the seventies from the necessity to process data structures with complex interrelations. Nowadays, various variants of these languages can be found...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Abstract. Current practice in Web application development is based on the skills of the individual programmers and often does not apply the principles of software engineering. The ...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...