— This paper describes an innovative approach to network testing based on automatically generating and analyzing state machine models of network behavior. The models are generate...
Nancy D. Griffeth, Yuri Cantor, Constantinos Djouv...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
In the last few years there has been a great amount of interest in Random Constraint Satisfaction Problems, both from an experimental and a theoretical point of view. Quite intrigu...
Dimitris Achlioptas, Lefteris M. Kirousis, Evangel...
A given entity, representing a person, a location or an organization, may be mentioned in text in multiple, ambiguous ways. Understanding natural language requires identifying whe...
The paper describes a conceptual framework for model-driven development based on concise application of UML and modeling tool functionality. A case study of modeling software for l...