Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces. (arXiv:2109.10964v4 [cs.LG] UPDATED)

Web: http://arxiv.org/abs/2109.10964

Many real world scientific and industrial applications require optimizing
multiple competing black-box objectives. When the objectives are
expensive-to-evaluate, multi-objective Bayesian optimization (BO) is a popular
approach because of its high sample efficiency. However, even with recent
methodological advances, most existing multi-objective BO methods perform
poorly on search spaces with more than a few dozen parameters and rely on
global surrogate models that scale cubically with the number of observations.
In this work we propose MORBO, a scalable method for multi-objective …

arxiv bayesian lg optimization search