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Related Questions
- How does domain knowledge about the objective function's landscape influence the selection of acquisition functions in Bayesian optimization?
- Can you provide examples of domain-specific acquisition functions that leverage prior knowledge about the problem's characteristics?
- How can domain knowledge about the noise level, correlations, or other properties of the objective function inform the choice of acquisition functions?
- What are some common pitfalls to avoid when using domain knowledge to inform acquisition function selection in Bayesian optimization?
- How can domain knowledge about the relationship between input variables and the objective function be used to guide the choice of acquisition functions?
- Can you discuss the trade-offs between using domain knowledge to inform acquisition function selection versus relying on default or general-purpose acquisition functions?
- How can domain knowledge about the problem's constraints or objectives be used to design custom acquisition functions that better suit the problem's needs?
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