The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Information about various visual attributes orientation and color is represented in the primate striate cortex (V1) before reaching extrastriate cortices. An important question re...
Youping Xiao, Ravi Rao, Guillermo A. Cecchi, Ehud ...
In this contribution, we explore the possibilities of learning in large-scale, multimodal processing systems operating under real-world conditions. Using an instance of a large-sca...