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Related Questions
- How do uncertainty sampling and query-by-committee methods differ in terms of their computational cost, and what are the implications of these differences for algorithm selection?
- Can you provide a detailed comparison of the computational costs associated with uncertainty sampling and query-by-committee methods in the context of active learning?
- How does the choice of algorithm between uncertainty sampling and query-by-committee methods impact the trade-off between exploration and exploitation in active learning?
- What are the key factors that influence the computational cost of uncertainty sampling and query-by-committee methods, and how can they be optimized?
- How do the computational costs of uncertainty sampling and query-by-committee methods affect the scalability of active learning algorithms in large-scale problems?
- Can you discuss the relationship between the computational cost of uncertainty sampling and query-by-committee methods and the accuracy of the learned models?
- What are some strategies for reducing the computational cost of uncertainty sampling and query-by-committee methods in active learning, and how effective are they in practice?
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