Active Learning For Regression
Active Learning for Regression is an active learning approach that specifically addresses regression tasks by iteratively selecting the most informative instances to label in order to improve the performance of a regression model with minimal labeled data.
108
Publications
6.2K
Citations
300
Authors
152
Institutions
Publications per year
2017–2026
66
Parents
108
Active learning via transductive experimental design
Kai Yu, Jinbo Bi, Volker Tresp · 2006 · 356 citations
Logistic regression with an auxiliary data source
Xuejun Liao, Ya Xue, Lawrence Carin · 2005 · 202 citations
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152

Northwestern Polytechnical University
Xi'an, China
5 h-index
11 publications
421 citations

University of Trento
Trento, Italy
4 h-index
9 publications
416 citations

Huazhong University of Science and Technology
Wuhan, China
4 h-index
14 publications
1.2K citations

Southwest Jiaotong University
Chengdu, China
4 h-index
14 publications
360 citations
Tokyo Institute of Technology
Tokyo, Japan
4 h-index
5 publications
296 citations

Université Grenoble Alpes
Saint-Martin-d'Hères, France
3 h-index
7 publications
137 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
9 publications
168 citations
Duke University
Durham, United States
3 h-index
8 publications
806 citations
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Repository · 6 publications · 132 citations
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5 publications · 214 citations
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5 publications · 310 citations
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3 publications · 152 citations
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3 publications · 58 citations
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