In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
Abstract. We describe a general component software framework designed for demanding grid environments that provides optimal performance for the assembled component application. Thi...
Nathalie Furmento, Anthony Mayer, Stephen McGough,...
This paper proposes two new methods for optimizing objectives and constraints. The GP approach is very general and hardware resources in finite wordlength implementation of it allo...
In previous work, we proposed ValueCharts, a set of visualizations and interactive techniques to support the inspection of linear models of preferences. We now identify the need t...
: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...