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Related Questions
- Can you describe the concept of data curation in active learning?
- How do human annotators contribute to reducing data bias in active learning?
- What are some common heuristics used to determine which samples to select in active learning?
- How does active learning compare to traditional machine learning in terms of data annotation requirements?
- What are some potential ways to address the issue of annotator bias in human-annotated datasets in active learning?
- Can you explain how active learning can be applied to imbalanced datasets where one class has a vastly larger number of instances?
- What are some potential limitations of using active learning for mitigating data bias, such as the need for large quantities of high-quality annotations or the potential for human annotation errors to propagate into trained models?
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