Meta-Learning has been used to relate the performance of algorithms and the features of the problems being tackled. The knowledge in Meta-Learning is acquired from a set of meta-e...
One of the objectives of this paper is to verify whether it is possible to extract meaningful related tags from a limited set of tagged resources and from resources tagged by only ...
Abstract. This paper explores the capabilities of continuous time recurrent neural networks (CTRNNs) to display reinforcement learning-like abilities on a set of T-Maze and double ...
Words unknown to the lexicon present a substantial problem to part-of-speech tagging. In this paper we present a technique for fully unsupervised statistical acquisition of rules ...
The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular m...
Nigel Williams, Sebastian Zander, Grenville J. Arm...