Abstract Standard Bayesian optimization handles uncertainty by taking random samples of model parameters, but this random sampling creates noise. This noise can cause the optimizer to accidentally rank bad configurations above good ones and steer the search in the wrong direction. This issue is especially noticeable in complex tasks with many variables or when computational limits restrict the number of samples you can take.
This package implements OrthoBO, a framework introduced in this paper from May 2026.