: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
—Designing a sensor network congestion avoidance algorithm is a challenging task due to the application specific nature of these networks. The frequency of event sensing is a de...
: This paper presents an evolutionary algorithm applicable to the task of device adjustment in smart appliances ensembles. The algorithm requires very little environmental knowledg...
This paper deals with the reconstruction of T1-T2 correlation spectra in Nuclear Magnetic Resonance (NMR) spectroscopy. The ill-posed character of this inverse problem and its lar...
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...