144 citations · 966 across the 20 of their papers we have counts for
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On the Impossibility of Convex Inference in Human Computation
Nihar B. Shah, Dengyong Zhou
Human computation or crowdsourcing involves joint inference of the ground-truth-answers and the worker-abilities by optimizing an objective function, for instance, by maximizing th…
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing
Nihar B. Shah, Dengyong Zhou
Crowdsourcing has gained immense popularity in machine learning applications for obtaining large amounts of labeled data. Crowdsourcing is cheap and fast, but suffers from the prob…
Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing
Yuchen Zhang, Xi Chen, Dengyong Zhou +1
Crowdsourcing is a popular paradigm for effectively collecting labels at low cost. The Dawid-Skene estimator has been widely used for inferring the true labels from the noisy label…
Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling
Xi Chen, Qihang Lin, Dengyong Zhou
In crowd labeling, a large amount of unlabeled data instances are outsourced to a crowd of workers. Workers will be paid for each label they provide, but the labeling requester usu…