4 citations · 8 across the 4 of their papers we have counts for
4 papers
Estimating Treatment Effects Under Heterogeneous Interference
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu +3
Treatment effect estimation can assist in effective decision-making in e-commerce, medicine, and education. One popular application of this estimation lies in the prediction of the…
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…
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…
Multiview Representation Learning from Crowdsourced Triplet Comparisons
Xiaotian Lu, Jiyi Li, Koh Takeuchi +1
Crowdsourcing has been used to collect data at scale in numerous fields. Triplet similarity comparison is a type of crowdsourcing task, in which crowd workers are asked the questio…