Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of random measurements. Existing results in compressed sens...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
We consider the parametric minimum spanning tree problem, in which we are given a graph with edge weights that are linear functions of a parameter and wish to compute the sequenc...
Pankaj K. Agarwal, David Eppstein, Leonidas J. Gui...
This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
Abstract: Pseudorandom number generators are widely used in the area of simulation. Defective generators are still widely used in standard library programs, although better pseudor...