Accessing structured data in the form of ontologies requires training and learning formal query languages (e.g., SeRQL or SPARQL) which poses significant difficulties for non-expe...
In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Abstract. Data centric languages, such as recursive rule based languages, have been proposed to program distributed applications over networks. They simplify greatly the code, whic...
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...