Profile Bayesian Optimization for Expensive Computer Experiments

The article likely presents a novel approach to Bayesian optimization, specifically tailored for scenarios where evaluating the objective function (computer experiments) is computationally expensive. The focus is on improving the efficiency of the optimization process in such resource-intensive settings. The use of 'Profile' suggests a method that leverages a profile likelihood or similar technique to reduce the dimensionality or complexity of the optimization problem.

• •Focuses on optimizing computationally expensive computer experiments.
• •Likely introduces a novel Bayesian optimization technique.
• •Employs a 'Profile' method to improve efficiency, potentially reducing dimensionality.