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Related Questions
- What is the relationship between the acquisition function and the posterior distribution of the objective function in Bayesian optimization?
- Can you explain how the acquisition function uses the posterior distribution to balance exploration and exploitation in optimization problems?
- How does the acquisition function leverage the posterior distribution to determine the next point to evaluate in the search space?
- What are some common acquisition functions used in Bayesian optimization, and how do they utilize the posterior distribution?
- In what ways does the acquisition function adapt to changes in the posterior distribution during the optimization process?
- Can you provide examples of scenarios where the acquisition function's use of the posterior distribution leads to improved optimization performance?
- How does the acquisition function handle cases where the posterior distribution is multimodal or has a high variance?
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