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1. 1. A Theoretical Framework for Bayesian Optimization Convergence

   Master-uppsats, KTH/Optimeringslära och systemteori

   Författare :Alexandre Scotto Di Perrotolo; [2018]
   Nyckelord :;

   Sammanfattning : Bayesian optimization is a well known class of derivative-free optimization algorithms mainly used for expensive black-box objective functions. Despite their efficiency, they suffer from a lack of rigorous convergence criterion which makes them more prone to be used as modeling tools rather than optimizing tools. LÄS MER