4 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.HC2023★ 1 cited
Mitigating Voter Attribute Bias for Fair Opinion Aggregation
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
The aggregation of multiple opinions plays a crucial role in decision-making, such as in hiring and loan review, and in labeling data for supervised learning. Although majority vot…
cs.HC2023★ 4 cited
Mitigating Observation Biases in Crowdsourced Label Aggregation
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
Crowdsourcing has been widely used to efficiently obtain labeled datasets for supervised learning from large numbers of human resources at low cost. However, one of the technical c…