When facing the question of learning languages in realistic settings, one has to tackle several problems that do not admit simple solutions. On the one hand, languages are usually...
Leonor Becerra-Bonache, Colin de la Higuera, Jean-...
We consider PAC learning of simple cooperative games, in which the coalitions are partitioned into "winning" and "losing" coalitions. We analyze the complexity...
In this paper we examine a novel addition to the known methods for learning Bayesian networks from data that improves the quality of the learned networks. Our approach explicitly ...
Abstract: Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about com...
Stefan Schaal, Christopher G. Atkeson, Sethu Vijay...
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...