Unsupervised domain adaptation with post-adaptation labeled domain performance preservation
Unsupervised domain adaptation is a machine learning-oriented application that aims to transfer knowledge learned from a seen (source) domain with labeled data to an unseen (target) domain with only unlabeled data. Recently developed techniques apply adversarial learning to learn domain-transferable...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
|
| Series: | Machine Learning with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827022001141 |