One of the nice properties of kernel classifiers such as SVMs is that they often produce sparse solutions. However, the decision functions of these classifiers cannot always be u...
We present an information theoretic approach for learning a linear dimension reduction transform for object classification. The theoretic guidance of the approach is that the trans...
Non-stop and highly available applications need to be dynamically adapted to new conditions in their execution environment, to new user requirements or to some situations usually u...
Abstract. The aim of our research was to apply well-known data mining techniques (such as linear neural networks, multi-layered perceptrons, probabilistic neural networks, classifi...
Marcin Paprzycki, Ajith Abraham, Ruiyuan Guo, Srin...
In this paper, we present a deterministic dependency structure analyzer for Chinese. This analyzer implements two algorithms – Yamada and Nivre models – and two sorts of class...