A dimensionality reduction technique for unconstrained global optimization of functions with low effective dimensionality

We investigate the unconstrained global optimization of functions with low effective dimensionality, which are constant along certain (unknown) linear subspaces. Extending the technique of random subspace embeddings in Wang et al. (2016, J. Artificial Intelligence Res., 55, 361–387), we s...

詳細記述

書誌詳細
主要な著者: Cartis, C, Otemissov, A
フォーマット: Journal article
言語:English
出版事項: Oxford University Press 2021