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...
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| Materyal Türü: | Journal article |
| Dil: | English |
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Oxford University Press
2021
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