We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
This paper follows on from our previous work focused on formulating an efficient generic measure of user’s satisfaction (‘interest’) when playing predator/prey games. Viewin...
Human-robot interaction is a growing research domain; there are many approaches to robot design, depending on the particular aspects of interaction being focused on. In this paper...
In this paper, we propose a linguistically annotated reordering model for BTG-based statistical machine translation. The model incorporates linguistic knowledge to predict orders ...