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Related Questions
- What is the effect of under-sampling the objective function on the exploration-exploitation trade-off in Bayesian optimization?
- Can under-sampling lead to biased estimates of the objective function, and if so, how can this be mitigated?
- How does under-sampling impact the convergence rate of Bayesian optimization algorithms, and what are the implications for suboptimal solutions?
- In what scenarios is under-sampling more likely to result in suboptimal solutions, and how can these scenarios be identified?
- Can under-sampling be avoided or minimized through the use of alternative Bayesian optimization algorithms or techniques?
- What are the key differences between under-sampling and over-sampling in Bayesian optimization, and how do these differences impact solution quality?
- How can the effects of under-sampling be quantified and measured in Bayesian optimization, and what metrics can be used to evaluate solution quality?
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