The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Probabilistic logics have attracted a great deal of attention during the past few years. While logical languages have taken a central position in research on knowledge representati...
Arjen Hommersom, Nivea de Carvalho Ferreira, Peter...
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Cognitive Agents must be able to decide their actions based on their recognized states. In general, learning mechanisms are equipped for such agents in order to realize intellgent ...