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We consider the problem of accurately estimating the reliability of workers based on noisy labels they provide, which is a fundamental question in crowdsourcing.
Maximum likelihood estimation of observer error-rates using the EM algorithm
A. P. Dawid and A. M. Skene · 1979
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Estimating the error rates of diagnostic tests
Sui L Hui and Steven D Walter · 1980
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Optimal decision rules in uncertain dichotomous choice situations
Shmuel Nitzan and Jacob Paroush · 1982
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Optimizing group judgmental accuracy in the presence of interdependencies
Lloyd Shapley and Bernard Grofman · 1984
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Inferring ground truth from subjective labelling of venus images
Padhraic Smyth, Usama Fayyad, Michael Burl, Pietro Perona, and Pierre Baldi · 1995
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A cautionary note on the robustness of latent class models for estimating diagnostic error without a gold standard
Paul S Albert and Lori E Dodd · 2004
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Introduction to non-parametric estimation
Alexandre B. Tsybakov · 2008
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Whose vote should count more: Optimal integration of labels from labelers of unknown expertise
Jacob Whitehill, Ting-fan Wu, Jacob Bergsma, Javier R Movellan, and Paul L Ruvolo · 2009
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Learning from crowds
Vikas C Raykar, Shipeng Yu, Linda H Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, and Linda Moy · 2010
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Online crowdsourcing: rating annotators and obtaining cost-effective labels
Peter Welinder and Pietro Perona · 2010
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Who moderates the moderators?: crowdsourcing abuse detection in user-generated content
Arpita Ghosh, Satyen Kale, and R. Preston McAfee · 2011
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Iterative learning for reliable crowdsourcing systems
David R. Karger, Sewoong Oh, and Devavrat Shah · 2011
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Variational inference for crowdsourcing
Qiang Liu, Jian Peng, and Alex T Ihler · 2012
Efficient crowdsourcing for multi-class labeling
David R Karger, Sewoong Oh, and Devavrat Shah · 2013
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Recursive fact-finding: A streaming approach to truth estimation in crowdsourcing applications
Dong Wang, Tarek Abdelzaher, Lance Kaplan, and Charu C Aggarwal · 2013
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Budget-optimal task allocation for reliable crowdsourcing systems
David R Karger, Sewoong Oh, and Devavrat Shah · 2014
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Spectral methods meet EM: A provably optimal algorithm for crowdsourcing
Yuchen Zhang, Xi Chen, Dengyong Zhou, and Michael I Jordan · 2014
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Regularized minimax conditional entropy for crowdsourcing
Dengyong Zhou, Qiang Liu, John C Platt, Christopher Meek, and Nihar B Shah · 2014
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Cited alongside, same era.
Aggregating crowdsourced binary ratings
Nilesh Dalvi, Anirban Dasgupta, Ravi Kumar, and Vibhor Rastogi · 2013
Cited alongside, same era.
Gao Chao and Zhou Dengyong · 2015
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