Maximum Margin Classification
Maximum Margin Classification is a classification method that belongs to the family of linear discriminant models and is distinguished by its objective of maximizing the geometric margin between the separating hyperplane and the nearest data points of each class to enhance generalization performance.
377
Publications
41.5K
Citations
908
Authors
397
Institutions
Publications per year
2017–2026
76
Parents
377
A training algorithm for optimal margin classifiers
Bernhard E. Boser, Isabelle Guyon, Vladimir Vapnik · 1992 · 11.6K citations
Boosting the margin: a new explanation for the effectiveness of voting methods
Peter L. Bartlett, Yoav Freund, Wee Sun Lee et al. · The Annals of Statistics · 1998 · 2.3K citations · Full text
Support Vector Machines for Multiple-Instance Learning
Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann · 2002 · 1.4K citations
Large margin classification using the perceptron algorithm
Yoav Freund, Robert E. Schapire · 1998 · 1.1K citations
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397
China Agricultural University
Beijing, China
11 h-index
29 publications
1K citations

Chinese Academy of Sciences
Beijing, China
11 h-index
22 publications
1.1K citations
Tsinghua University
Beijing, China
9 h-index
16 publications
668 citations

Xidian University
Xi'an, China
8 h-index
33 publications
656 citations
Nanjing University of Science and Technology
Nanjing, China
8 h-index
18 publications
815 citations

Australian National University
Canberra, Australia
7 h-index
18 publications
10.5K citations
University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
12 publications
2.2K citations

Royal Holloway University of London
Egham, United Kingdom
6 h-index
6 publications
2.5K citations
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22 publications · 688 citations
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17 publications · 433 citations
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Repository · 16 publications · 599 citations
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12 publications · 632 citations
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13 publications · 901 citations
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