An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
— Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a cost effe...
Dirk Gorissen, Luciano De Tommasi, Jeroen Croon, T...
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
This paper presents a new unified design flow developed within the Perplexus project that aims to accelerate parallelizable data-intensive applications in the context of ubiquitous...
— Enriched with more and more intelligent devices modern homes rapidly transform into smart environments. Their growing capabilities enable the implementation of a new generation...
Grzegorz Lehmann, Andreas Rieger, Marco Blumendorf...