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» Bayesian Evolutionary Optimization Using Helmholtz Machines
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ICML
2003
IEEE
13 years 9 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens
SEAL
2010
Springer
13 years 3 months ago
Bayesian Reliability Analysis under Incomplete Information Using Evolutionary Algorithms
During engineering design, it is often difficult to quantify product reliability because of insufficient data or information for modeling the uncertainties. In such cases, one need...
Rupesh Kumar Srivastava, Kalyanmoy Deb
LION
2009
Springer
129views Optimization» more  LION 2009»
13 years 11 months ago
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
IJON
1998
158views more  IJON 1998»
13 years 4 months ago
Bayesian Kullback Ying-Yang dependence reduction theory
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Lei Xu