In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learni...
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
In this paper, we present a learning approach to the scenario template task of information extraction, where information filling one template could come from multiple sentences. ...
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...