4 papers
Local Preferential Bayesian Optimization
Johanna Menn, Miriam Kober, Paul Brunzema +2
Bayesian optimization (BO) is a popular and effective approach for tuning expensive, noisy experiments, but requires the formulation of an explicit objective function. Preferential…
Preferential Bayesian Optimization with Crash Feedback
Johanna Menn, David Stenger, Sebastian Trimpe
Bayesian optimization is a popular black-box optimization method for parameter learning in control and robotics. It typically requires an objective function that reflects the user'…
Lipschitz Safe Bayesian Optimization for Automotive Control
Johanna Menn, Pietro Pelizzari, Michael Fleps-Dezasse +1
Controller tuning is a labor-intensive process that requires human intervention and expert knowledge. Bayesian optimization has been applied successfully in different fields to aut…
Safety in safe Bayesian optimization and its ramifications for control
Christian Fiedler, Johanna Menn, Sebastian Trimpe
A recurring and important task in control engineering is parameter tuning under constraints, which conceptually amounts to optimization of a blackbox function accessible only throu…