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Related Questions
- What are the primary differences between acquisition functions, such as UCB, EI, and Thompson Sampling, and how do they impact the optimization process?
- How do the characteristics of the objective function, such as its shape and noise level, influence the choice of acquisition function?
- What are the trade-offs between exploration and exploitation in Bayesian optimization, and how do different acquisition functions balance these competing objectives?
- Can you explain the concept of 'eluder dimension' and its impact on the performance of acquisition functions in high-dimensional optimization problems?
- How do acquisition functions handle non-stationarity and changing objective functions, and what strategies can be employed to adapt to these changes?
- What are the computational complexities of different acquisition functions, and how do they impact the scalability of Bayesian optimization in large-scale problems?
- Can you discuss the role of exploration-exploitation trade-offs in acquisition functions, and how they relate to the concept of 'informedness' in Bayesian optimization?
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