In this paper, we present an automated text classification system for the classification of biomedical papers. This classification is based on whether there is experimental eviden...
S. Sathiya Keerthi, Chong Jin Ong, Keng Boon Siah,...
We present in this paper a method to introduce a priori knowledge into reinforcement learning using temporally extended actions. The aim of our work is to reduce the learning time ...
The definition of new concepts or roles for which extensional knowledge become available can turn out to be necessary to make a DL ontology evolve. In this paper we reformulate thi...
Knowledge elicitation is known to be a difficult task and thus a major bottleneck in building a knowledge base. Machine learning has long ago been proposed as a way to alleviate th...
Martin Mozina, Matej Guid, Jana Krivec, Aleksander...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...