Manifold Regularized Experimental Design for Active Learning
Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one samp...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 26(2017), 2 vom: 15. Feb., Seite 969-981 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2017
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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