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Related Questions
- What are the implications of using different acquisition functions in Bayesian optimization, such as Expected Improvement or Probability of Improvement, on the balance between exploration and exploitation?
- How can the use of a surrogate model's uncertainty estimates, such as variance or standard deviation, be leveraged to inform the exploration-exploitation trade-off?
- What are some strategies for adapting the exploration-exploitation balance over the course of the optimization process, such as using a schedule or a dynamic threshold?
- Can the use of multi-objective optimization techniques, such as Pareto optimization, help to balance exploration and exploitation in Bayesian optimization?
- How can the choice of surrogate model, such as a Gaussian process or a neural network, impact the balance between exploration and exploitation?
- What are some techniques for incorporating prior knowledge or domain expertise into the Bayesian optimization process to inform the exploration-exploitation trade-off?
- Can the use of ensemble methods, such as bagging or boosting, be used to combine the predictions of multiple surrogate models and improve the balance between exploration and exploitation?
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