Structure-Preserved Multi-source Domain Adaptation

By Hongfu Liu, Ming Shao, Yun Raymond Fu. 2016

32 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Epidemiology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. David Edwin Carlson
2. Geraldine Dawson
3. Deqing Wang
4. Fuzhen Zhuang
5. Yongchun Zhu
6. Yitong Li
7. Michael Murias
8. Songcan Chen

Citations in the corpus

• Recent Advances in Open Set Recognition: A Survey (2018, background): “This seems to have the flavor of domain adaptation having multiple source domains and one target domain (mS1T) [172], [173], [174], [175] to some extent.”
• Extracting Relationships by Multi-Domain Matching (2018, background): “Clustering [25] and late fusion [1] approaches have also been evaluated.”
• Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources (2019, background): “MUDA also develops with theoretical supports (Ben-David et al. 2010; Blitzer et al. 2008; Liu, Shao, and Fu 2016).”