2nd collaboration workshop on Reinforcement Learning for Autonomous Accelerators (RL4AA'24)

Robustly Safe Bayesian Optimization

Feb 6, 2024, 9:50 AM

20m

Blue lecture hall (Universität Salzburg (Paris-Lodron-Universität))

Student Talk Student Session

Speaker

Jannis Lübsen (TUHH/DESY)

Description

Safety guarantees for Gaussian processes require the assumption that the true hyperparameters are known. However, this assumption usually does not hold in practice. In this talk, a method is introduced to overcome this issue which estimates confidence intervals of hyperparameters from their posterior distributions. Finally, it can be shown that via appropriate scaling safeness can be robustly guaranteed with high probability.

Presentation materials

main.pdf