Bayesian Approach to Continuous Global and Stochastic Optimization
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 17)
Consider a family C A of continuous functions f = f(x), x ∈ A ⊂ R m . Assume a possibility to evaluate f at any fixed point x n , n = 1,..., N, where N is the total number of observations.
KeywordsGlobal Minimum Bayesian Method Conditional Expectation Risk Function Wiener Process
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer Science+Business Media Dordrecht 1997