An ensemble of classifiers is a set of classifiers whose predictions are combined in some way to classify new instances. Early research has shown that, in general, an ensemble of ...
In this paper we introduce a novel method to address minimization of static and dynamic MRFs. Our approach is based on principles from linear programming and, in particular, on pr...
In this paper, we propose a technique for segmenting visual textures using features extracted from the reponses of Ga,bor filters, appropria.tely selectecl to be tuned to texture ...
OWL 2 RL was standardized as a less expressive but scalable subset of OWL 2 that allows a forward-chaining implementation. However, building an enterprise-scale forward-chaining ba...
Abstract— We describe a model for planar distributed assembly, in which agents move randomly and independently on a twodimensional grid, joining square blocks together to form a ...