Bayesian Optimization with Local GPR for Efficient Search

The author proposes a Bayesian optimization method that limits the search region to lower dimensions and utilizes local Gaussian process regression (LGPR) to improve search efficiency. By training the LGPR model on a local subset of data, prediction accuracy is enhanced, reducing time complexity.