4 papers
BayeSQP: Bayesian Optimization through Sequential Quadratic Programming
Paul Brunzema, Sebastian Trimpe
We introduce BayeSQP, a novel algorithm for general black-box optimization that merges the structure of sequential quadratic programming with concepts from Bayesian optimization. B…
Local Entropy Search over Descent Sequences for Bayesian Optimization
David Stenger, Armin Lindicke, Alexander von Rohr +1
Searching large and complex design spaces for a global optimum can be infeasible and unnecessary. A practical alternative is to iteratively refine the neighborhood of an initial de…
Sailing Towards Zero-Shot State Estimation using Foundation Models Combined with a UKF
Tobin Holtmann, David Stenger, Andres Posada-Moreno +2
State estimation in control and systems engineering traditionally requires extensive manual system identification or data-collection effort. However, transformer-based foundation m…
Early Stopping Bayesian Optimization for Controller Tuning
David Stenger, Dominik Scheurenberg, Heike Vallery +1
Manual tuning of performance-critical controller parameters can be tedious and sub-optimal. Bayesian Optimization (BO) is an increasingly popular practical alternative to automatic…