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Jessa Bekker

5 papers hereh-index 81.2k citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author1

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.AI2

identity via Semantic Scholar / OpenAlex

activity
20162025
most citedLearning from positive and unlabeled data: a survey

552 citations · 564 across the 5 of their papers we have counts for

collaborators
Showing 2018Show all

3 papers · 1 filter

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.