Our work focuses on the design of interaction techniques for large information spaces. Our goal is not to define yet another visualization technique but to provide insights for th...
Abstract. In this paper, we discuss approximation spaces in a granular computing framework. Such approximation spaces generalise the approaches to concept approximation existing in...
: Assessing the quality of conceptual models is key to ensure that conceptual models can be used effectively as a basis for understanding, agreement and construction of information...
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Abstract-- Successful investment management relies on allocating assets so as to beat the stock market. Asset classes are affected by different market dynamics or latent trends. Th...
Ruairi de Frein, Konstantinos Drakakis, Scott Rick...