23 citations · 36 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 23 cited
A Variational Approach for Learning from Positive and Unlabeled Data
Hui Chen, Fangqing Liu, Yin Wang +2
Learning binary classifiers only from positive and unlabeled (PU) data is an important and challenging task in many real-world applications, including web text classification, dise…
cs.LG2014★ 13 cited
An Active Learning Approach for Jointly Estimating Worker Performance and Annotation Reliability with Crowdsourced Data
Liyue Zhao, Yu Zhang, Gita Sukthankar
Crowdsourcing platforms offer a practical solution to the problem of affordably annotating large datasets for training supervised classifiers. Unfortunately, poor worker performanc…