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Related Questions
- How do probabilistic models in Bayesian optimization handle the issue of increasing uncertainty in high-dimensional search spaces?
- What are some common techniques used to reduce the dimensionality of the search space in Bayesian optimization?
- Can you explain how the use of surrogates or approximations can help alleviate the curse of dimensionality in Bayesian optimization?
- How do Bayesian optimization algorithms like Expected Improvement (EI) and Probability of Improvement (PI) address the curse of dimensionality?
- What role does regularization play in mitigating the effects of the curse of dimensionality in Bayesian optimization?
- Can you discuss the impact of using different types of probabilistic models, such as Gaussian processes or random forests, on the curse of dimensionality in Bayesian optimization?
- How do Bayesian optimization algorithms handle the trade-off between exploration and exploitation in high-dimensional search spaces?
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