On Bayes approach to optimization
Petr Volf · ASEP · 2014
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.