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Related Questions
- How can active learning techniques be used to reduce the annotation cost and improve the accuracy of machine learning models?
- What are some common active learning strategies for selecting the most informative samples for annotation?
- Can active learning techniques help mitigate the issue of bias in machine learning models by selecting a diverse set of samples for annotation?
- How does active learning compare to other techniques for reducing bias in machine learning, such as debiasing algorithms or data preprocessing?
- What are some challenges and limitations of using active learning techniques for reducing bias in machine learning models?
- Can active learning be used in conjunction with other techniques, such as transfer learning or ensemble methods, to further reduce bias?
- How can the effectiveness of active learning techniques for reducing bias be evaluated and measured in practice?
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