A probabilistic framework of transfer learning- theory and application
abstract: Transfer learning refers to statistical machine learning methods that integrate the knowledge of one domain (source domain) and the data of another domain (target domain) in an appropriate way, in order to develop a model for the target domain that is better than a model using the data of...
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| Format: | Doctoral Thesis |
| Language: | English |
| Published: |
2015
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| Online Access: | http://hdl.handle.net/2286/R.I.36040 |