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Efficient PAC Learning from the Crowd with Pairwise Comparison. (arXiv:2011.01104v3 [cs.LG] UPDATED)
Jan. 21, 2022, 2:11 a.m. | Jie Shen, Shiwei Zeng
cs.LG updates on arXiv.org arxiv.org
Efficient PAC learning of threshold functions is arguably one of the most
important problems in machine learning. With the unprecedented growth of
large-scale data sets, it has become ubiquitous to appeal to the crowd wisdom
for data annotation, and the central problem that attracts a surge of recent
interests is how one can learn the underlying hypothesis from the highly noisy
crowd annotation while well-controlling the annotation cost. On the other hand,
a large body of recent works have investigated …
More from arxiv.org / cs.LG updates on arXiv.org
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