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}
}
• Chao Gao, Yu Lu
• Published in ICML 2016
• Mathematics, Computer Science
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

#### Paper Mentions

Optimal Inference in Crowdsourced Classification via Belief Propagation
• Computer Science, Mathematics
• IEEE Transactions on Information Theory
• 2018
A Permutation-Based Model for Crowd Labeling: Optimal Estimation and Robustness
• Computer Science, Mathematics
• IEEE Transactions on Information Theory
• 2021
Improving the Quality of Crowdsourced Image Labeling via Label Similarity
• Computer Science
• Journal of Computer Science and Technology
• 2017
Collusion-Proof Result Inference in Crowdsourcing
• Computer Science
• Journal of Computer Science and Technology
• 2018

#### References

SHOWING 1-10 OF 27 REFERENCES
Aggregating crowdsourced binary ratings
• Computer Science
• WWW '13
• 2013
Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing
• Computer Science, Mathematics
• J. Mach. Learn. Res.
• 2016
Learning from the Wisdom of Crowds by Minimax Entropy
• Computer Science, Mathematics
• NIPS
• 2012
Learning From Crowds