552 citations · 1.1k across the 22 of their papers we have counts for
Showing 2018 · cs.LGShow all
3 papers · 2 filters
cs.LG2018★ 552 cited
Learning from positive and unlabeled data: a survey
Jessa Bekker, Jesse Davis
Learning from positive and unlabeled data or PU learning is the setting where a learner only has access to positive examples and unlabeled data. The assumption is that the unlabele…
cs.LG2018★ 3 cited
Beyond the Selected Completely At Random Assumption for Learning from Positive and Unlabeled Data
Jessa Bekker, Pieter Robberechts, Jesse Davis
Most positive and unlabeled data is subject to selection biases. The labeled examples can, for example, be selected from the positive set because they are easier to obtain or more…
cs.LG2018★ 8 cited
Learning from Positive and Unlabeled Data under the Selected At Random Assumption
Jessa Bekker, Jesse Davis
For many interesting tasks, such as medical diagnosis and web page classification, a learner only has access to some positively labeled examples and many unlabeled examples. Learni…