The standard model of supervised learning assumes that training and test data are drawn from the same underlying distribution. This paper explores an application in which a second...
Acoustic events produced in meeting-room-like environments may carry information useful for perceptually aware interfaces. In this paper, we focus on the problem of combining diffe...
Naïve Bayes (NB) classifier has long been considered a core methodology in text classification mainly due to its simplicity and computational efficiency. There is an increasing n...
A fundamental problem in peer-to-peer networks is how to locate appropriate peers efficiently to answer a specific query request. This paper proposes a model in which semantically...
Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that e...
Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan ...