A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an eï¬...
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
We propose a mathematical framework for query selection as a mechanism for reducing the cost of constructing information retrieval test collections. In particular, our mathematica...
Mehdi Hosseini, Ingemar J. Cox, Natasa Milic-Frayl...
The increased availability of online knowledge has led to the design of several algorithms that solve a variety of tasks by harvesting the Semantic Web, i.e., by dynamically select...
Marta Sabou, Jorge Gracia, Sofia Angeletou, Mathie...