We introduce an approach to visualize stationary 2D vector fields with global uncertainty obtained by considering the transport of local uncertainty in the flow. For this, we ex...
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Parallel programming is a requirement in the multi-core era. One of the most promising techniques to make parallel programming available for the general users is the use of parall...
Angeles G. Navarro, Rafael Asenjo, Siham Tabik, Ca...
We study the task of randomness extraction from sources which are distributed uniformly on an unknown algebraic variety. In other words, we are interested in constructing a functi...
Loop nest optimization is a combinatorial problem. Due to the growing complexity of modern architectures, it involves two increasingly difficult tasks: (1) analyzing the profita...