Expected Model Change
Expected Model Change is an acquisition function in active learning that quantifies the anticipated parameter update of a model upon training on a candidate unlabeled instance, distinguishing itself from other selection criteria by estimating the magnitude of change in model parameters as a proxy for informativeness.
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1.2K
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85
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52
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2017–2026
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Maximizing Expected Model Change for Active Learning in Regression
Wenbin Cai, Ya Zhang, Jun Zhou · 2013 · 179 citations
S. Çağatay Bağçacı, İsmail Yücel, Eren Düzenli et al. · Atmospheric Research · 2021 · 179 citations · Full text
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Shanghai Jiao Tong University
Shanghai, China
2 h-index
5 publications
727 citations
Mediterranean Institute for Advanced Studies
Esporles, Spain
1 h-index
2 publications
90 citations
Royal Netherlands Meteorological Institute
De Bilt, The Netherlands
1 h-index
2 publications
20 citations
Barts Health NHS Trust
London, United Kingdom
1 h-index
2 publications
68 citations
Institute of Psychology, Chinese Academy of Sciences
Beijing, China
1 h-index
2 publications
244 citations
Shandong Jiaotong University
Jinan, China
1 h-index
2 publications
190 citations

Royal Stoke University Hospital
Stoke-on-Trent, United Kingdom
1 h-index
3 publications
102 citations
University of Chinese Academy of Sciences
Beijing, China
1 h-index
2 publications
244 citations
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Repository · 3 publications · 81 citations
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2 publications · 70 citations
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1 publications · 20 citations
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1 publications · 95 citations
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1 publications · 179 citations
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