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» Using Gaussian Processes to Optimize Expensive Functions
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IPPS
2007
IEEE
14 years 2 months ago
Parallel Processing for Multi-objective Optimization in Dynamic Environments
This paper deals with the use of parallel processing for multi-objective optimization in applications in which the objective functions, the restrictions, and hence also the soluti...
Mario Cámara, Julio Ortega, Francisco de To...
ICASSP
2008
IEEE
14 years 2 months ago
Belief propagation distributed estimation in sensor networks: An optimized energy accuracy tradeoff
The estimation error performance of Gaussian belief propagation based distributed estimation in a large sensor network employing random sleep strategies is explicitly evaluated fo...
John MacLaren Walsh, Phillip A. Regalia
CEC
2007
IEEE
14 years 2 months ago
A Utile Function Optimizer
Abstract— We recast the problem of unconstrained continuous evolutionary optimization as inference in a fixed graphical model. This approach allows us to address several pervasi...
Christopher K. Monson, Kevin D. Seppi, James L. Ca...
EPS
1997
Springer
13 years 12 months ago
Tracking Extrema in Dynamic Environments
Typical applications of evolutionary optimization involve the off-line approximation of extrema of static multi-modal functions. Methods which use a variety of techniques to self-...
Peter J. Angeline
BMCBI
2006
120views more  BMCBI 2006»
13 years 7 months ago
A factor analysis model for functional genomics
Background: Expression array data are used to predict biological functions of uncharacterized genes by comparing their expression profiles to those of characterized genes. While b...
Rafal Kustra, Romy Shioda, Mu Zhu