3 papers
math.OC2025
Safe Bayesian optimization across noise models via scenario programming
Abdullah Tokmak, Thomas B. Schön, Dominik Baumann
Safe Bayesian optimization (BO) with Gaussian processes is an effective tool for tuning control policies in safety-critical real-world systems, specifically due to its sample effic…
eess.SY2025
Towards safe control parameter tuning in distributed multi-agent systems
Abdullah Tokmak, Thomas B. Schön, Dominik Baumann
Many safety-critical real-world problems, such as autonomous driving and collaborative robots, are of a distributed multi-agent nature. To optimize the performance of these systems…
cs.LG2025
Safe exploration in reproducing kernel Hilbert spaces
Abdullah Tokmak, Kiran G. Krishnan, Thomas B. Schön +1
Popular safe Bayesian optimization (BO) algorithms learn control policies for safety-critical systems in unknown environments. However, most algorithms make a smoothness assumption…