Spoken Language Understanding aims at mapping a natural language spoken sentence into a semantic representation. In the last decade two main approaches have been pursued: generati...
Marco Dinarelli, Alessandro Moschitti, Giuseppe Ri...
This paper introduces a domain ontology to describe learning material that compose a course, capable of providing adaptive e-learning environments and reusable educational resourc...
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...
Abstract. In this paper, we describe the features of the Timed Abstract State Machine toolset. The toolset implements the features of the Timed Abstract State Machine (TASM) langua...
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...