-
1
-
-
84867117736
-
How to grade a test without knowing the answers-a bayesian graphical model for adaptive crowdsourcing and aptitude testing
-
Bachrach, Y.; Graepel, T.; Minka, T.; and Guiver, J. 2012. How to grade a test without knowing the answers-a bayesian graphical model for adaptive crowdsourcing and aptitude testing. In Proceedings of the 29th International Conference on Machine Learning (ICML-12), 1183-1190.
-
(2012)
Proceedings of the 29th International Conference on Machine Learning (ICML-12)
, pp. 1183-1190
-
-
Bachrach, Y.1
Graepel, T.2
Minka, T.3
Guiver, J.4
-
6
-
-
84880366208
-
A convex formulation for learning from crowds
-
Kajino, H.; Tsuboi, Y.; and Kashima, H. 2012. A convex formulation for learning from crowds. In AAAI.
-
(2012)
AAAI
-
-
Kajino, H.1
Tsuboi, Y.2
Kashima, H.3
-
8
-
-
84871089459
-
The face of quality in crowdsourcing relevance labels: Demographics, personality and labeling accuracy
-
ACM
-
Kazai, G.; Kamps, J.; and Milic-Frayling, N. 2012. The face of quality in crowdsourcing relevance labels: Demographics, personality and labeling accuracy. In Proceedings of the 21st ACM international conference on Information and knowledge management, 2583-2586. ACM.
-
(2012)
Proceedings of the 21st ACM international conference on Information and knowledge management
, pp. 2583-2586
-
-
Kazai, G.1
Kamps, J.2
Milic-Frayling, N.3
-
9
-
-
84875650055
-
An analysis of human factors and label accuracy in crowdsourcing relevance judgments
-
Kazai, G.; Kamps, J.; and Milic-Frayling, N. 2013. An analysis of human factors and label accuracy in crowdsourcing relevance judgments. Information retrieval 16(2):138-178.
-
(2013)
Information retrieval
, vol.16
, Issue.2
, pp. 138-178
-
-
Kazai, G.1
Kamps, J.2
Milic-Frayling, N.3
-
13
-
-
84954098959
-
Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation
-
ACM
-
Ma, F.; Li, Y.; Li, Q.; Qiu, M.; Gao, J.; Zhi, S.; Su, L.; Zhao, B.; Ji, H.; and Han, J. 2015. Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 745-754. ACM.
-
(2015)
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 745-754
-
-
Ma, F.1
Li, Y.2
Li, Q.3
Qiu, M.4
Gao, J.5
Zhi, S.6
Su, L.7
Zhao, B.8
Ji, H.9
Han, J.10
-
16
-
-
77951954464
-
Learning from crowds
-
Raykar, V. C.; Yu, S.; Zhao, L. H.; Valadez, G. H.; Florin, C.; Bogoni, L.; and Moy, L. 2010a. Learning from crowds. Journal of Machine Learning Research 11:1297-1322.
-
(2010)
Journal of Machine Learning Research
, vol.11
, pp. 1297-1322
-
-
Raykar, V. C.1
Yu, S.2
Zhao, L. H.3
Valadez, G. H.4
Florin, C.5
Bogoni, L.6
Moy, L.7
-
17
-
-
77951954464
-
Learning from crowds
-
(Apr)
-
Raykar, V. C.; Yu, S.; Zhao, L. H.; Valadez, G. H.; Florin, C.; Bogoni, L.; and Moy, L. 2010b. Learning from crowds. Journal of Machine Learning Research 11(Apr):1297-1322.
-
(2010)
Journal of Machine Learning Research
, vol.11
, pp. 1297-1322
-
-
Raykar, V. C.1
Yu, S.2
Zhao, L. H.3
Valadez, G. H.4
Florin, C.5
Bogoni, L.6
Moy, L.7
-
19
-
-
65449144451
-
Get another label? improving data quality and data mining using multiple, noisy labelers
-
New York, NY, USA: ACM
-
Sheng, V. S.; Provost, F.; and Ipeirotis, P. G. 2008. Get another label? improving data quality and data mining using multiple, noisy labelers. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '08, 614-622. New York, NY, USA: ACM.
-
(2008)
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '08
, pp. 614-622
-
-
Sheng, V. S.1
Provost, F.2
Ipeirotis, P. G.3
-
20
-
-
84909581998
-
Community-based bayesian aggregation models for crowdsourcing
-
New York, NY, USA: ACM
-
Venanzi, M.; Guiver, J.; Kazai, G.; Kohli, P.; and Shokouhi, M. 2014. Community-based bayesian aggregation models for crowdsourcing. In Proceedings of the 23rd International Conference on World Wide Web, WWW '14, 155-164. New York, NY, USA: ACM.
-
(2014)
Proceedings of the 23rd International Conference on World Wide Web, WWW '14
, pp. 155-164
-
-
Venanzi, M.1
Guiver, J.2
Kazai, G.3
Kohli, P.4
Shokouhi, M.5
-
21
-
-
84982683097
-
Time-sensitive bayesian information aggregation for crowdsourcing systems
-
Venanzi, M.; Guiver, J.; Kohli, P.; and Jennings, N. R. 2016. Time-sensitive bayesian information aggregation for crowdsourcing systems. Journal of Artificial Intelligence Research 56:517-545.
-
(2016)
Journal of Artificial Intelligence Research
, vol.56
, pp. 517-545
-
-
Venanzi, M.1
Guiver, J.2
Kohli, P.3
Jennings, N. R.4
-
23
-
-
85162055266
-
The multidimensional wisdom of crowds
-
Welinder, P.; Branson, S.; Perona, P.; and Belongie, S. J. 2010. The multidimensional wisdom of crowds. In Advances in neural information processing systems, 2424-2432.
-
(2010)
Advances in neural information processing systems
, pp. 2424-2432
-
-
Welinder, P.1
Branson, S.2
Perona, P.3
Belongie, S. J.4
-
24
-
-
77951951247
-
Whose vote should count more: Optimal integration of labels from labelers of unknown expertise
-
Whitehill, J.; Ruvolo, P.; Wu, T.; Bergsma, J.; and Movellan, J. R. 2009. Whose vote should count more: Optimal integration of labels from labelers of unknown expertise. In 23rd Annual Conference on Neural Information Processing Systems, NIPS'09, 2035-2043.
-
(2009)
23rd Annual Conference on Neural Information Processing Systems, NIPS'09
, pp. 2035-2043
-
-
Whitehill, J.1
Ruvolo, P.2
Wu, T.3
Bergsma, J.4
Movellan, J. R.5
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