This paper proposes a two-step graph partitioning method to discover constrained clusters with an objective function that follows the well-known minmax clustering principle. Compar...
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
In some domains, Information Extraction (IE) from texts requires syntactic and semantic parsing. This analysis is computationally expensive and IE is potentially noisy if it applie...
Recent developments in software and hardware changed the way database systems are built and operate. In this paper we present database architectures based on the Client Server par...