Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
We investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a Bernoulli-Gaussian pro...
This paper presents the adaptation model used in NUCLEO, a pilot e-learning environment that is currently being developed at the Complutense University of Madrid. The NUCLEO syste...
Although they have been the main server technology for many years, multiprocessors are undergoing a renaissance due to multi-core chips and the attractive scalability properties of...
— We present a method for fast analysis of signal and power integrity based on a recently developed multilayered finite difference method (M-FDM). In order to accurately model m...