The case for fully Bayesian optimisation in small-sample trials. (arXiv:2208.13960v1 [cs.LG])

While sample efficiency is the main motive for use of Bayesian optimisation
when black-box functions are expensive to evaluate, the standard approach based
on type II maximum likelihood (ML-II) may fail and result in disappointing
performance in small-sample trials. The paper provides three compelling reasons
to adopt fully Bayesian optimisation (FBO) as an alternative. First, failures
of ML-II are more commonplace than implied by the existing studies using the
contrived settings. Second, FBO is more robust than ML-II, and the …

arxiv bayesian case small