Expected Error Reduction
Expected Error Reduction is an active learning criterion that belongs to the class of query strategies and is distinguished by its objective of selecting unlabeled instances that minimize the expected generalization error of the model after labeling.
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Publications
416
Citations
21
Authors
7
Institutions
Publications per year
2017–2026
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6
Hierarchical Subquery Evaluation for Active Learning on a Graph
Oisin Mac Aodha, Neill D. F. Campbell, Jan Kautz et al. · 2014 · 98 citations · Full text
Scalable Active Learning by Approximated Error Reduction
Weijie Fu, Meng Wang, Shijie Hao et al. · 2018 · 42 citations
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IBM Research - Thomas J. Watson Research Center, United States
1 publications · 18 citations
1
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1–5 of 21
7
University College London
London, United Kingdom
1 h-index
4 publications
392 citations

Hefei University of Technology
Hefei, China
1 h-index
4 publications
168 citations
University of Bern
Bern, Switzerland
1 h-index
1 publications
139 citations
China Academy of Launch Vehicle Technology
Beijing, China
1 h-index
2 publications
156 citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
1 h-index
2 publications
278 citations

Northwestern Polytechnical University
Xi'an, China
1 h-index
3 publications
234 citations
University of Southern California
Los Angeles, United States
1 h-index
1 publications
41 citations
1–7 of 7
Repository · 1 publications · 139 citations
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1 publications · 78 citations
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