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TSP
2010
15 years 17 days ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
SIGECOM
2004
ACM
96views ECommerce» more  SIGECOM 2004»
15 years 11 months ago
A stochastic programming approach to scheduling in TAC SCM
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...
WISE
2002
Springer
15 years 10 months ago
Applying the Site Information to the Information Retrieval from the Web
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...
Yasuhito Asano, Hiroshi Imai, Masashi Toyoda, Masa...
IJAR
2008
118views more  IJAR 2008»
15 years 5 months ago
Dynamic multiagent probabilistic inference
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...
Xiangdong An, Yang Xiang, Nick Cercone
ATMOS
2010
183views Optimization» more  ATMOS 2010»
15 years 4 months ago
The Complexity of Integrating Routing Decisions in Public Transportation Models
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...
Marie Schmidt, Anita Schöbel