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Related Questions
- How does the choice of acquisition function impact the convergence of Bayesian optimization for expensive-to-evaluate objective functions?
- Can you explain the trade-off between exploration and exploitation in Bayesian optimization, and how it relates to the number of iterations?
- What are some common techniques used to handle high-dimensional objective functions in Bayesian optimization, and how do they affect the number of iterations required?
- How does the initialization of the search space and the prior distribution affect the performance of Bayesian optimization in terms of the number of iterations?
- Can you discuss the role of surrogate models in Bayesian optimization, and how they impact the number of iterations required to find an optimal solution?
- What are some strategies for adaptively adjusting the number of iterations in Bayesian optimization to balance exploration and exploitation?
- How does the concept of 'budget' or 'computational cost' relate to Bayesian optimization, and how does it influence the number of iterations for expensive objective functions?
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