0431513 20240103204612.620141013235959.9 000356417900185 6 s. C cav_un_epca*0431512978-80-244-4209-91078-1083OlomoucPalacký University2014TalašováJ. optimization Bayes method nonparametric regression. cav_un_auth*0101227 Stochastická informatika Department of Stochastic Informatics SI SI Department of Stochastic Informatics Volf Petr UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2014/SI/volf-0431513.pdf cav_un_auth*0292652 GA13-14445S GA ČR 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. cav_un_auth*0306071 MME 2014. International Conference Mathematical Methods in Economics /32./ 10.09.2014-12.09.2014 Olomouc CZ BB 2015 1 PR RVO:67985556 http://hdl.handle.net/11104/0237110 S 2014 000356417900185 WOS cav_un_epca*0431512 Proceedings of 32nd International Conference Mathematical Methods in Economics MME 2014 978-80-244-4209-9 1078 1083 Olomouc Palacký University 2014 Talašová J. 340 Stoklasa J. 340 Talášek T. 340