Reducing search space for high-dimensional Bayesian optimization by Variational Auto-Encoder

Abstract

Bayesian optimization is used in various fields, but it is known to not work well in high-dimensional search spaces. One approach to address this problem is to transform the high-dimensional input space into a low-dimensional latent space and perform Bayesian optimization in the latter low-dimensional space. In this study, as one such approach, we propose a new high-dimensional Bayesian optimization method that integrates manifold Bayesian optimization and predictive distribution reconstruction.