We present a discriminative method for learning selectional preferences from unlabeled text. Positive examples are taken from observed predicate-argument pairs, while negatives ar...
In this paper, a `market trading' technique is integrated with the techniques of rule discovery and refinement for data mining. A classifier system-inspired model, the market...
This paper investigates a machine learning approach for temporally ordering and anchoring events in natural language texts. To address data sparseness, we used temporal reasoning ...
Inderjeet Mani, Marc Verhagen, Ben Wellner, Chong ...
In this thesis we compare several machine learning techniques for evaluating external skeletal fixation proposals. We experimented in the context of dog bone fractures but the pot...
Ning Suo, Khaled Rasheed, Walter D. Potter, Dennis...
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...