Entropy Minimization
Entropy Minimization is a regularization strategy in semi-supervised learning that enforces confident predictions on unlabeled data by reducing the entropy of the model's output probability distribution, thereby promoting low-density separation between classes.
890
Publications
59.9K
Citations
2.3K
Authors
833
Institutions
Publications per year
2017–2026
365
890
1–5 of 890
2.3K
Institute of Chemical and Engineering Sciences, Singapore
31 publications · 1.2K citations
20
h-index
15
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Institute of Chemical and Engineering Sciences, Singapore
20 publications · 960 citations
14
h-index
13
h-index
12
h-index
1–5 of 2.3K
833
National University of Singapore
Singapore, Singapore
21 h-index
75 publications
3.7K citations
Institute of Chemical and Engineering Sciences
Singapore, Singapore
16 h-index
69 publications
1.5K citations
Tsinghua University
Beijing, China
15 h-index
28 publications
892 citations

Centre National de la Recherche Scientifique
Paris, France
14 h-index
44 publications
3.6K citations
Naval University of Engineering
Wuhan, China
14 h-index
42 publications
1.7K citations
Quaid-i-Azam University
Islamabad, Pakistan
14 h-index
44 publications
4K citations

King Abdulaziz University
Jeddah, Saudi Arabia
13 h-index
34 publications
2.7K citations
Agency for Science, Technology and Research
Singapore, Singapore
13 h-index
43 publications
785 citations
1–8 of 833
Repository · 76 publications · 3.7K citations
28
h-index
13 publications · 579 citations
13
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13 publications · 1.7K citations
13
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12 publications · 421 citations
12
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11 publications · 379 citations
11
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