Linear Maximum Margin Classifier for Learning from Uncertain Data
In this paper, we propose a maximum margin classifier that deals with uncertainty in data input. More specifically, we reformulate the SVM framework such that each training example can be modeled by a multi-dimensional Gaussian distribution described by its mean vector and its covariance matrix-the...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 40(2018), 12 vom: 14. Dez., Seite 2948-2962 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2018
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't |
| Accès en ligne |
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