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Related Questions
- How does the choice of acquisition function in Bayesian optimization affect the trade-off between iterations and sample size?
- Can you explain the concept of 'elaboration cost' in Bayesian optimization and how it relates to the trade-off between iterations and sample size?
- How does the use of a probabilistic model in Bayesian optimization impact the trade-off between iterations and sample size compared to grid search?
- What is the relationship between the number of iterations and the sample size in Bayesian optimization, and how does it impact the accuracy of the optimization result?
- Can you provide an example of a scenario where Bayesian optimization would be more computationally efficient than grid search due to a better trade-off between iterations and sample size?
- How does the choice of kernel in Bayesian optimization affect the trade-off between iterations and sample size, and what are the implications for computational efficiency?
- Can you discuss the role of hyperparameter tuning in Bayesian optimization and how it impacts the trade-off between iterations and sample size, compared to grid search?
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