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Crowdsourcing has become an effective and popular tool for human-powered computation to label large datasets.
On the distribution of the number of successes in independent trials
W. Hoeffding · 1956
Earlier work this paper cites.
Maximum likelihood from incomplete data via the em algorithm
A. P. Dempster, N. M. Laird, and D. B. Rubin · 1977
Earlier work this paper cites.
Maximum Likelihood Estimation of Observer Error-Rates Using the EM Algorithm
A. P. Dawid and A. M. Skene · 1979
Earlier work this paper cites.
Learning from noisy examples
D. Angluin and P. Laird · 1988
Earlier work this paper cites.
Inferring Ground Truth from Subjective Labelling of Venus Images
P. Smyth, U. Fayyad, M. Burl, P. Perona, and P. Baldi · 1995
Earlier work this paper cites.
A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models
J. A. Bilmes · 1998
Earlier work this paper cites.
Concentration
C. McDiarmid · 1998
Earlier work this paper cites.
Learning with Multiple Labels
R. Jin and Z. Ghahramani · 2002
Earlier work this paper cites.
Get Another Label? Improving Data Quality and Data Mining Using Multiple, Noisy Labelers Categories and Subject Descriptors
C. S. Sheng and F. Provost · 2008
Earlier work this paper cites.
Cheap and Fast - But is it Good ? Evaluating Non-Expert Annotations for Natural Language Tasks
R. Snow, B. O. Connor, D. Jurafsky, and A. Y. Ng · 2008
Earlier work this paper cites.
Good learners for evil teachers
O. Dekel and O. Shamir · 2009
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Whose Vote Should Count More : Optimal Integration of Labels from Labelers of Unknown Expertise
J. Whitehill, P. Ruvolo, T. Wu, J. Bergsma, and J. Movellan · 2009
Cited alongside, same era.
Old and new concentration inequalities, Chapter 2 in Complex Graphs and Networks
F. Chung and L. Liu · 2010
Cited alongside, same era.
Learning From Crowds
V. C. Raykar, S. Yu, L. H. Zhao, C. Florin, L. Bogoni, and L. Moy · 2010
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The Multidimensional Wisdom of Crowds
P. Welinder, S. Branson, S. Belongie, and P. Perona · 2010
Cited alongside, same era.
Modeling annotator expertise : Learning when everybody knows a bit of something
Y. Yan, R. Rosales, G. Fung, M. Schmidt, G. Hermosillo, L. Bogoni, L. Moy, and J. G. Dy · 2010
Cited alongside, same era.
How to grade a test without knowing the answers — a bayesian graphical model for adaptive crowdsourcing and aptitude testing
Y. Bachrach, T. Graepel, T. Minka, and J. Guiver · 2012
Later among the works it cites.
Pattern classification
R. O. Duda, P. E. Hart, and D. G. Stork · 2012
Later among the works it cites.
Variational Inference for Crowdsourcing
Q. Liu, J. Peng, and A. Ihler · 2012
Later among the works it cites.
Learning from the Wisdom of Crowds by Minimax Entropy
D. Zhou, J. Platt, S. Basu, and Y. Mao · 2012
Later among the works it cites.
Optimistic Knowledge Gradient Policy for Optimal Budget Allocation in Crowdsourcing
X. Chen, Q. Lin, and D. Zhou · 2013
Later among the works it cites.
Aggregating crowdsourced binary ratings
N. Dalvi, A. Dasgupta, R. Kumar, and V. Rastogi · 2013
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Approximating the Wisdom of the Crowd
S. Ertekin, H. Hirsh, and C. Rudin · 2011
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Iterative learning for reliable crowdsourcing systems
D. R. Karger, S. Oh, and D. Shah · 2011
Cited alongside, same era.
Tail and Concentration Inequalities
H. Q. Ngo · 2011
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Active Learning from Crowds
Y. Yan, R. Rosales, G. Fung, and J. G. Dy · 2011
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Essai sur l’application de l’analyse à la probabilité des décisions rendues à la pluralité des voix
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Adaptive Task Assignment for Crowdsourced Classification
C. Ho, S. Jabbari, and J. W. Vaughan · 2013
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Learning with noisy labels
N. Natarajan, I. Dhillon, P. Ravikumar, and A. Tewari · 2013
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Minimax optimal convergence rates for estimating ground truth from crowdsourced labels
C. Gao and D. Zhou · 2014
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