We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
In this paper we investigate a discriminative approach to feature weighting for topic identification using minimum classification error (MCE) training. Our approach learns featu...
Current statistical machine translation systems usually extract rules from bilingual corpora annotated with 1-best alignments. They are prone to learn noisy rules due to alignment...
It is well known that editing techniques can be applied to (large) sets of prototypes in order to bring the error rate of the Nearest Neighbour classifier close to the optimal Ba...
Abstract. One question that arises if we want to evolve generation techniques to accommodate Web ontologies is how to capture and expose the relevant ontology content to the user. ...