Meta-design is an emerging conceptual framework aimed at defining and creating socio-technical environments as living entities. It extends existing design methodologies focused on ...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
Identifying co-varying causal elements in very high dimensional feature space with internal structures, e.g., a space with as many as millions of linearly ordered features, as one...
Visualization interfaces that offer multiple coordinated views on a particular set of data items are useful for navigating and exploring complex information spaces. In this paper ...
Using artificial neural networks for Electroencephalogram (EEG) signal interpretation is a very challenging tasks for several reasons. The first class of reasons refers to the nat...