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  • In many real optimization problems we have not full information on the objective function and can afford to evaluate it at just a few points. Then, certain assumptions on the objective function must be done. This could be taken as a prior information in a Bayes scheme. The Bayes approach to optimization then offers the way of effective search for the extremal point. We describe the technique how to mapproach the optimum using the Gauss process or a regression-like models.
  • In many real optimization problems we have not full information on the objective function and can afford to evaluate it at just a few points. Then, certain assumptions on the objective function must be done. This could be taken as a prior information in a Bayes scheme. The Bayes approach to optimization then offers the way of effective search for the extremal point. We describe the technique how to mapproach the optimum using the Gauss process or a regression-like models. (en)
Title
  • On Bayes approach to optimization
  • On Bayes approach to optimization (en)
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  • On Bayes approach to optimization
  • On Bayes approach to optimization (en)
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  • RIV/67985556:_____/14:00431513!RIV15-GA0-67985556
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  • I, P(GA13-14445S)
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  • 34241
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  • RIV/67985556:_____/14:00431513
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  • optimization; Bayes method; nonparametric regression. (en)
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  • [4F269C4DFF89]
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  • Olomouc
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  • Olomouc
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  • Proceedings of 32nd International Conference Mathematical Methods in Economics MME 2014
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  • Volf, Petr
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  • Univerzita Palackého v Olomouci
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  • 978-80-244-4209-9
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