Semi-Supervised Learning on Riemannian Manifolds.
We consider the general problem of utilizing both labeled and unlabeled data to improve classification accuracy. Under the assumption that the data lie on a submanifold in a high dimensional space, we develop an algorithmic framework to classify a partially labeled data set in a principled manner. T...
| Published in: | Machine learning. 56, 1-3 (2004). |
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| Main Author: | |
| Format: | Article |
| Language: | English |
| Subjects: |