We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Building 3D models of real-world objects by assembling views taken by a range sensor promises to be a more efficient method than manually producing CAD drawings. In this technique...
On the basis of detailed analysis of reaction times and neurophysiological data from tasks involving choice, it has been proposed that the brain implements an optimal statistical ...
In the past, we have observed several large blackouts, i.e. loss of power to large areas. It has been noted by several researchers that these large blackouts are a result of a cas...
This paper describes an approach for generating customized benchmark suites from a software architecture description following a Model Driven Architecture (MDA) approach. The benc...