Research graph
References from Learning From Crowds With Multiple Feature Dynamic Fusion-Based Annotation Generation. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1109/jas.2022.105434
10.1109/jas.2022.105434 · External reference
10.1145/1401890.1401965
10.1145/1401890.1401965 · External reference
Learning to predict from crowdsourced data
External reference
10.1109/tkde.2014.2327026
10.1109/tkde.2014.2327026 · External reference
10.1109/tkde.2015.2504974
10.1109/tkde.2015.2504974 · External reference
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10.14778/3055540.3055547 · External reference
10.1609/aaai.v28i2.19016
10.1609/aaai.v28i2.19016 · External reference
10.1007/s10115-022-01743-z
10.1007/s10115-022-01743-z · External reference
10.1016/j.ins.2022.05.066
10.1016/j.ins.2022.05.066 · External reference
10.1145/2488388.2488414
10.1145/2488388.2488414 · External reference
10.1007/s10115-019-01386-7
10.1007/s10115-019-01386-7 · External reference
10.1109/tnnls.2021.3082496
10.1109/tnnls.2021.3082496 · External reference
Learning from crowds
2010 · External reference
Spectral methods meet em: A provably optimal algorithm for crowdsourcing
2016 · External reference
10.1109/tkde.2019.2951668
10.1109/tkde.2019.2951668 · External reference
10.1145/1557019.1557053
10.1145/1557019.1557053 · External reference
Learning from the wisdom of crowds by minimax entropy
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Aggregating ordinal labels from crowds by minimax conditional entropy
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10.1145/1458082.1458165
10.1145/1458082.1458165 · External reference
10.1109/icdm.2011.133
10.1109/icdm.2011.133 · External reference
10.1609/aaai.v26i1.8105
10.1609/aaai.v26i1.8105 · External reference
10.1109/tkde.2018.2860992
10.1109/tkde.2018.2860992 · External reference
10.1007/s11704-022-2245-8
10.1007/s11704-022-2245-8 · External reference
10.1609/aaai.v27i1.8456
10.1609/aaai.v27i1.8456 · External reference
10.1609/aaai.v32i1.11506
10.1609/aaai.v32i1.11506 · External reference
10.24963/ijcai.2020/210
10.24963/ijcai.2020/210 · External reference
10.1007/s10994-022-06185-w
10.1007/s10994-022-06185-w · External reference
10.1609/aaai.v35i7.16730
10.1609/aaai.v35i7.16730 · External reference
10.1109/tnnls.2022.3168696
10.1109/tnnls.2022.3168696 · External reference
10.1007/s10994-022-06211-x
10.1007/s10994-022-06211-x · External reference
10.1609/aaai.v38i15.29613
10.1609/aaai.v38i15.29613 · External reference
10.1109/tpami.2024.3388209
10.1109/tpami.2024.3388209 · External reference
10.1609/aaai.v34i04.5898
10.1609/aaai.v34i04.5898 · External reference
10.1145/3394486.3403167
10.1145/3394486.3403167 · External reference
10.1007/s10115-022-01701-9
10.1007/s10115-022-01701-9 · External reference
10.1109/allerton.2011.6120180
10.1109/allerton.2011.6120180 · External reference
10.1109/tpami.2018.2860987
10.1109/tpami.2018.2860987 · External reference
10.1016/j.patcog.2024.111034
10.1016/j.patcog.2024.111034 · External reference
10.2307/2346806
10.2307/2346806 · External reference
10.1109/cvpr.2019.01150
10.1109/cvpr.2019.01150 · External reference
10.1145/3491101.3519614
10.1145/3491101.3519614 · External reference
10.1109/cse/euc.2019.00077
10.1109/cse/euc.2019.00077 · External reference
10.1109/icpr56361.2022.9956439
10.1109/icpr56361.2022.9956439 · External reference
10.1016/j.engappai.2022.105624
10.1016/j.engappai.2022.105624 · External reference
10.1007/s10489-022-03433-3
10.1007/s10489-022-03433-3 · External reference
10.1007/978-3-031-24386-8_17
10.1007/978-3-031-24386-8_17 · External reference
The multidimensional wisdom of crowds
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Modeling annotator expertise: Learning when everybody knows a bit of something
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10.1007/s10994-013-5412-1
10.1007/s10994-013-5412-1 · External reference
Learning from crowds with dual-view k-nearest neighbor
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10.1016/j.patcog.2023.109525
10.1016/j.patcog.2023.109525 · External reference
10.1609/aaai.v34i04.5898
10.1609/aaai.v34i04.5898 · External reference
10.1109/tmi.2016.2528120
10.1109/tmi.2016.2528120 · External reference
10.21655/ijsi.1673-7288.00270
10.21655/ijsi.1673-7288.00270 · External reference
10.1109/tbdata.2024.3378100
10.1109/tbdata.2024.3378100 · External reference
10.1609/aaai.v32i1.11756
10.1609/aaai.v32i1.11756 · External reference
10.52202/079017-3085
10.52202/079017-3085 · External reference
10.1609/aaai.v32i1.11506
10.1609/aaai.v32i1.11506 · External reference
Gaussian process classification and active learning with multiple annotators
External reference
Learning with noisy labels revisited: A study using real-world human annotations
2021 · External reference
Generalized cross entropy loss for training deep neural networks with noisy labels
External reference
10.1109/cvpr.2017.240
10.1109/cvpr.2017.240 · External reference
10.1145/2588555.2610509
10.1145/2588555.2610509 · External reference
Adversarial crowdsourcing through robust rank-one matrix completion
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Max-mig: An information theoretic approach for joint learning from crowds
2019 · External reference
Bayesian classifier combination
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Exploiting worker correlation for label aggregation in crowdsourcing
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Estimating instance-dependent Bayes-label transition matrix using a deep neural network
2021 · External reference
10.1109/cvpr.2016.90
10.1109/cvpr.2016.90 · External reference
10.1609/aaai.v32i1.11506
10.1609/aaai.v32i1.11506 · External reference
