In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
In this paper we argue for UML-based metamodeling and pattern-based graph transformation techniques in computer-based systems development through an illustrative example from the ...
Tivadar Szemethy, Gabor Karsai, Daniel Balasubrama...
The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds ...
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
The infinite hidden Markov model is a nonparametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov...
Jurgen Van Gael, Yunus Saatci, Yee Whye Teh, Zoubi...