We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
In this paper, we combine two approaches to handling uncertainty: we use techniques for finding optimal solutions in the expected sense to solve combinatorial optimization proble...
Michael Benisch, Amy R. Greenwald, Victor Narodits...
In recent years, several information retrieval methods using information about the Web-links are developed, such as HITS and Trawling. In order to analyze the Web-links dividing i...
Cooperative multiagent probabilistic inference can be applied in areas such as building surveillance and complex system diagnosis to reason about the states of the distributed unc...
To model and solve optimization problems arising in public transportation, data about the passengers is necessary and has to be included in the models in any phase of the planning...