A survey on heterogeneous transfer learning
Abstract Transfer learning has been demonstrated to be effective for many real-world applications as it exploits knowledge present in labeled training data from a source domain to enhance a model’s performance in a target domain, which has little or no labeled target training data. Utilizing a label...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2017-09-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40537-017-0089-0 |