Deep transfer learning on continual learning
Artificial intelligent agents acting in the real world interact with a multitude of data streams. As a result, they must attain, accumulate and record various tasks from non-stationary data distributions. In addition, self-governing computational agents must acquire an understanding of new experienc...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/171082 |
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| Institution: | Nanyang Technological University |
| Language: | English |