Search Results for author:
Found 2 papers, 0 papers with code
Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling
The performance analysis of the method is based on posterior sampling theory and its practical efficiency is illustrated using a numerical example of a highly nonlinear dynamical car-trailer system.
Advancing Bayesian Optimization: The Mixed-Global-Local (MGL) Kernel and Length-Scale Cool Down
Bayesian Optimization (BO) has become a core method for solving expensive black-box optimization problems.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
