Active Learning For Classification
Active Learning for Classification is a machine learning paradigm within supervised classification that iteratively selects the most informative instances for labeling to improve model performance while minimizing annotation effort.
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70.6K
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3K
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958
Institutions
Publications per year
2017–2026
523
Parents
1.2K
Improving Generalization with Active Learning
David Cohn, Les Atlas, Richard E. Ladner · Machine Learning · 1994 · 1.3K citations · Full text
Less is More: Active Learning with Support Vector Machines
Greg Schohn, David Cohn · 2000 · 776 citations
Improving generalization with active learning
David Cohn, Les Atlas, Richard E. Ladner · Machine Learning · 1994 · 737 citations
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Carnegie Mellon University
Pittsburgh, United States
24 h-index
72 publications
4.6K citations
The University of Texas at Austin
Austin, United States
22 h-index
58 publications
4.4K citations

University of Trento
Trento, Italy
20 h-index
49 publications
3.9K citations
Microsoft (United States)
Redmond, United States
18 h-index
50 publications
4.3K citations

Chinese Academy of Sciences
Beijing, China
17 h-index
45 publications
2.1K citations
Wuhan University
Wuhan, China
16 h-index
60 publications
2.9K citations
Arizona State University
Tempe, United States
15 h-index
41 publications
2K citations
Nanyang Technological University
Singapore, Singapore
14 h-index
32 publications
1.5K citations
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Repository · 60 publications · 3.3K citations
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33 publications · 3.7K citations
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23 publications · 1.3K citations
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Conference · 22 publications · 726 citations
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17 publications · 953 citations
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