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Mitigating Voter Attribute Bias for Fair Opinion Aggregation
The experimental results suggest that the combination of Soft D&S and data splitting as a fairness option is effective for dense data, whereas weighted majority voting is effective for sparse data.
Mitigating Observation Biases in Crowdsourced Label Aggregation
Crowdsourcing has been widely used to efficiently obtain labeled datasets for supervised learning from large numbers of human resources at low cost.
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