Global optimization: a machine learning approach
Many approaches for addressing global optimization problems typically rely on relaxations of nonlinear constraints over specific mathematical primitives. This is restricting in applications with constraints that are implicit or consist of more general primitives. Trying to address such limitations,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer US
2024
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| Online Access: | https://hdl.handle.net/1721.1/157394 |