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Arxiv
3d
173
Image Credit: Arxiv
Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
- Offline design optimization problem arises in numerous science and engineering applications.
- Surrogate functions are used to predict and maximize the target objective over candidate designs.
- A theoretical framework is presented to understand offline black-box optimization.
- A black-box gradient matching algorithm is proposed to improve surrogate models for offline optimization.
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