We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
Problems that can be sampled randomly are a good source of test suites for comparing quality of constraint satisfaction techniques. Quasigroup problems are representatives of struc...
Abstract. We examine to what extent implementation of timed automata can be achieved using the standard semantics and appropriate modeling, instead of introducing new semantics. We...
The present paper presents the structure of a cross-linguistic database of production data. The database contains annotated texts collected from a sample of fifteen different langu...
In this paper we discuss the prospects of using marker based Augmented Reality for context aware applications on mobile phones. We also present the UMAR, a conceptual framework fo...