The emerging Model-Driven Engineering paradigm advocates the use of models as first-class citizens in the software development process, while artifacts such as documentation and so...
Currently several computational problems require high processing power to handle huge amounts of data, although underlying core algorithms appear to be rather simple. Especially i...
Lars Wienbrandt, Stefan Baumgart, Jost Bissel, Car...
, Yunde Jia Model structure selection is currently an open problem in modeling data via Gaussian Mixture Models (GMM). This paper proposes a discriminative method to select GMM st...
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Virtual machines are a promising technology to overcome some of the problems found in current Grid infrastructures, like heterogeneity, performance partitioning or application iso...
Antonio J. Rubio-Montero, Eduardo Huedo, Rub&eacut...