The Knowledge Discovery Toolbox (KDT) enables domain experts to perform complex analyses of huge datasets on supercomputers using a high-level language without grappling with the ...
Despite of their applicability betweennness constraints have (to the authorās knowledge) hardly been considered from the random structures point of view. They are essentially diļ...
This paper deals with the roles of assumption, mathematical models, and experimental control in Pattern Recognition. In order to base the discussion on actual examples, three stud...
In this paper we present techniques to significantly improve the space complexity of several ordered tree comparison algorithms without sacrificing the corresponding time complexit...
We study the complexity of the model checking problem, for fixed models A, over certain fragments L of first-order logic, obtained by restricting which of the quantifiers and boole...