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» Using Gaussian Processes to Optimize Expensive Functions
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IPPS
2007
IEEE
15 years 8 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...
114
Voted
ICASSP
2008
IEEE
15 years 8 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
15 years 8 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
15 years 6 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
119
Voted
BMCBI
2006
120views more  BMCBI 2006»
15 years 2 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