We use graphical models to explore the question of how people learn simple causal relationships from data. The two leading psychological theories can both be seen as estimating th...
This paper explores the relationship between various measures of unsupervised part-of-speech tag induction and the performance of both supervised and unsupervised parsing models t...
William P. Headden III, David McClosky, Eugene Cha...
Abstract. Among others, Alferes et al. (1998) presented an approach for updating logic programs with sets of rules based on dynamic logic programs. We syntactically redefine dynami...
Thomas Eiter, Michael Fink, Giuliana Sabbatini, Ha...
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
Stochastically searching the space of candidate clauses is an appealing way to scale up ILP to large datasets. We address an approach that uses a Bayesian network model to adaptive...