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Related Questions
- What strategies do probabilistic models in Bayesian optimization use to mitigate the effects of the curse of dimensionality in high-dimensional search spaces?
- How do Bayesian optimization algorithms adapt to high-dimensional spaces where the number of features exceeds the number of data points?
- Can you explain the concept of dimensionality reduction in the context of Bayesian optimization and how it helps with the curse of dimensionality?
- In high-dimensional spaces, how do probabilistic models in Bayesian optimization handle the issue of overfitting?
- What is the role of probabilistic surrogate models in addressing the curse of dimensionality in Bayesian optimization?
- Can you discuss the use of Gaussian processes in Bayesian optimization and how they handle high-dimensional search spaces?
- How do Bayesian optimization methods balance exploration and exploitation in high-dimensional spaces with many local optima?
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