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Related Questions
- How do surrogate models adapt to changing objective functions in dynamic environments?
- What are the differences between neural network-based surrogate models and traditional Gaussian process-based ones?
- Can surrogate models be used to integrate multiple objectives or constraints in Bayesian optimization?
- How do surrogate models affect the convergence behavior of the optimization process?
- What are some common applications of surrogate models in practice, such as design optimization and hyperparameter tuning?
- How do surrogate models handle high-dimensional search spaces and large datasets?
- Can surrogate models be used to reduce the sample complexity of Bayesian optimization in expensive-to-evaluate settings?
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