- A gate level probabilistic error propagation model is presented which takes as input the Boolean function of the gate, the signal and error probabilities of the gate inputs, and ...
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...
Visualizations are highly valuable in improving the understanding, as well as the analysis of a variety of physical phenomena. Two such applications can be as a pedagogical tool f...
J. Eskil Bendz, Hilton G. Fernandes, Marcelo Kn&ou...
Via an oracle experiment, we show that the upper bound on accuracy of a CCG parser is significantly lowered when its search space is pruned using a supertagger, though the supert...
The reliability of file systems depends in part on how well they propagate errors. We develop a static analysis technique, EDP, that analyzes how file systems and storage device d...