1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2020
Mixed Set Domain Adaptation
Sitong Mao, Keli Zhang, Fu-lai Chung
In the settings of conventional domain adaptation, categories of the source dataset are from the same domain (or domains for multi-source domain adaptation), which is not always tr…
cs.LG2020★ 1 cited
Against Adversarial Learning: Naturally Distinguish Known and Unknown in Open Set Domain Adaptation
Sitong Mao, Xiao Shen, Fu-lai Chung
Open set domain adaptation refers to the scenario that the target domain contains categories that do not exist in the source domain. It is a more common situation in the reality co…
cs.LG2020
Deep Adversarial Domain Adaptation Based on Multi-layer Joint Kernelized Distance
Sitong Mao, Jiaxin Chen, Xiao Shen +1
Domain adaptation refers to the learning scenario that a model learned from the source data is applied on the target data which have the same categories but different distribution.…