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Related Questions
- What are some strategies to reduce the need for human annotation in active learning?
- How can the use of weak supervision techniques, such as transfer learning, help alleviate the annotation burden?
- What are some techniques for selecting the most informative samples for human annotation in active learning?
- Can the use of active learning algorithms that adapt to changing data distributions help reduce the need for re-annotation?
- How can the annotation process be made more efficient through the use of automated data preprocessing and cleaning techniques?
- What role can transfer learning and few-shot learning play in reducing the need for human annotation in active learning?
- Are there any techniques for leveraging unlabeled data to improve the efficiency of human annotation in active learning?
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