On the basis of a case-study, we demonstrate the usefulness of topology invariants for model-driven systems development. Considering a graph grammar semantics for a relevant fragme...
The objective of this paper is to study the existing methods for unsupervised object recognition and image categorization and propose a model that can learn directly from the outp...
: Narrowing the wide conceptual gap between problem and implementation domains is considered a significant factor within software engineering. Currently, such a relation is often o...
We present a functional DBPL in the style of FP that facilitates the definition of precise semantics and opens up opportunities for far-reaching optimizations. The language is int...
To model combinatorial decision problems involving uncertainty and probability, we extend the stochastic constraint programming framework proposed in [Walsh, 2002] along a number ...