Simplification of mixture models has recently emerged as an important issue in the field of statistical learning. The heavy computational demands of using large order models dro...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
This paper describes work in progress to develop a component-based software infrastructure, called Padico, for computational grids based on the CORBA Component Model from the OMG....
There are a number of competing component models in use today. Most are language-independent, but also platform-dependent and not designed to support a tool-based development para...
Abstract. Extensible Component Platforms support the discovery, installation, starting, uninstallation of components at runtime. Since they are often targeted at mobile resource-co...