We introduce a novel data-driven mean-shift belief propagation
(DDMSBP) method for non-Gaussian MRFs, which
often arise in computer vision applications. With the aid
of scale sp...
As modern supercomputing systems reach the peta-flop performance range, they grow in both size and complexity. This makes them increasingly vulnerable to failures from a variety ...
Greg Bronevetsky, Daniel Marques, Keshav Pingali, ...
This paper is devoted to sequential decision problems with imprecise probabilities. We study the problem of determining an optimal strategy according to the Hurwicz criterion in de...
Abstract. Nonlinear component analysis is a popular nonlinear feature extraction method. It generally uses eigen-decomposition technique to extract the principal components. But th...
Group action recognition is a challenging task in computer vision due to the large complexity induced by multiple motion patterns. This paper aims at analyzing group actions in vid...