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» A Bayesian Approach to Tackling Hard Computational Problems
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GECCO
2006
Springer
170views Optimization» more  GECCO 2006»
14 years 2 months ago
How an optimal observer can collapse the search space
Many metaheuristics have difficulty exploring their search space comprehensively. Exploration time and efficiency are highly dependent on the size and the ruggedness of the search...
Christophe Philemotte, Hugues Bersini
GECCO
2008
Springer
196views Optimization» more  GECCO 2008»
13 years 11 months ago
ADANN: automatic design of artificial neural networks
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
Juan Peralta, Germán Gutiérrez, Arac...
MINENET
2005
ACM
14 years 4 months ago
Shrink: a tool for failure diagnosis in IP networks
Faults in an IP network have various causes such as the failure of one or more routers at the IP layer, fiber-cuts, failure of physical elements at the optical layer, or extraneo...
Srikanth Kandula, Dina Katabi, Jean-Philippe Vasse...
AINA
2010
IEEE
14 years 3 months ago
Active Data Selection for Sensor Networks with Faults and Changepoints
Abstract—We describe a Bayesian formalism for the intelligent selection of observations from sensor networks that may intermittently undergo faults or changepoints. Such active d...
Michael A. Osborne, Roman Garnett, Stephen J. Robe...
CVPR
2009
IEEE
14 years 2 months ago
Robust unsupervised segmentation of degraded document images with topic models
Segmentation of document images remains a challenging vision problem. Although document images have a structured layout, capturing enough of it for segmentation can be difficult....
Timothy J. Burns, Jason J. Corso