Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Learning Bayesian networks from data has been studied extensively in the evolutionary algorithm communities [Larranaga96, Wong99]. We have previously explored extending some of the...
In many data sharing settings, such as within the biological and biomedical communities, global data consistency is not always attainable: different sites' data may be dirty,...
Text mining concerns the discovery of knowledge from unstructured textual data. One important task is the discovery of rules that relate specific words and phrases. Although exist...
Conventional work on scientic discovery such as BACON derives empirical law equations from experimental data. In recent years, SDS introducing mathematical admissibility constrain...