We model ferromagnetic effects by using reduced scalar potential. An overlapping domain-decomposition technique is proposed to solve the underlying problem in unbounded domain. I...
In classifier combining, one tries to fuse the information that is given by a set of base classifiers. In such a process, one of the difficulties is how to deal with the variabilit...
Elzbieta Pekalska, Robert P. W. Duin, Marina Skuri...
Abstract. Recent findings in the domain of combining classifiers provide a surprising revision of the usefulness of diversity for modelling combined performance. Although there is ...
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...