Bound-constrained global optimization of functions with low effective dimensionality using multiple random embeddings
We consider the bound-constrained global optimization of functions with low effective dimensionality, that are constant along an (unknown) linear subspace and only vary over the effective (complement) subspace. We aim to implicitly explore the intrinsic low dimensionality of the constrained landscap...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Springer
2022
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