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

June 17, 2022, 1:11 a.m. | Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy

cs.LG updates on arXiv.org arxiv.org

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

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