Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification
Improvement guarantees for semi-supervised classifiers can currently only be given under restrictive conditions on the data. We propose a general way to perform semi-supervised parameter estimation for likelihood-based classifiers for which, on the full training set, the estimates are never worse th...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 38(2016), 3 vom: 05. März, Seite 462-75 |
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| Auteur principal: | |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2016
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article |
| Accès en ligne |
Volltext |