Drawing on the ‘representation’ TUI framework [21], this paper reports a study that investigated the concept of ‘representation location’ and its effect on interaction and...
Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Abstract. Machine learning methods were successfully applied in recent years for detecting new and unseen computer viruses. The viruses were, however, detected in small virus loade...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...