Feature uncertainty bounds for explicit feature maps and large robust nonlinear SVM classifiers
We consider the binary classification problem when data are large and subject to unknown but bounded uncertainties. We address the problem by formulating the nonlinear support vector machine training problem with robust optimization. To do so, we analyze and propose two bounding schemes for uncertai...
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| Published in: | Annals of mathematics and artificial intelligence Vol. 88; no. 1-3; pp. 269 - 289 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Cham
Springer International Publishing
01.03.2020
Springer Springer Nature B.V Springer Verlag |
| Subjects: | |
| ISSN: | 1012-2443, 1573-7470 |
| Online Access: | Get full text |
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