It is well-known that heuristic search in ILP is prone to plateau phenomena. An explanation can be given after the work of Giordana and Saitta: the ILP covering test is NP-complete...
Abstract. This paper describes Macquarie University’s Centre for Language Technology contribution to the PASCAL 2005 Recognizing Textual Entailment challenge. Our main aim was to...
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...