Corpus ID: 1387748

Exact Exponent in Optimal Rates for Crowdsourcing

@inproceedings{Gao2016ExactEI,
  title={Exact Exponent in Optimal Rates for Crowdsourcing},
  author={Chao Gao and Yu Lu and Dengyong Zhou},
  booktitle={ICML},
  year={2016}
}
In many machine learning applications, crowdsourcing has become the primary means for label collection. In this paper, we study the optimal error rate for aggregating labels provided by a set of non-expert workers. Under the classic Dawid-Skene model, we establish matching upper and lower bounds with an exact exponent $mI(\pi)$ in which $m$ is the number of workers and $I(\pi)$ the average Chernoff information that characterizes the workers' collective ability. Such an exact characterization of… Expand
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