Learning and Feature Selection under Budget Constraints in Crowdsourcing

HCOMP, pp. 159-168, 2016.

Cited by: 11|Views34
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Abstract:

The cost of data acquisition limits the amount of labeled data available for machine learning algorithms, both at the training and the testing phase. This problem is further exacerbated in real-world crowdsourcing applications where labels are aggregated from multiple noisy answers. We tackle classification problems where the underlying f...More

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