80 citations · 235 across the 18 of their papers we have counts for
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cs.LG2020★ 73 cited
Multi-source Domain Adaptation in the Deep Learning Era: A Systematic Survey
Sicheng Zhao, Bo Li, Colorado Reed +2
In many practical applications, it is often difficult and expensive to obtain enough large-scale labeled data to train deep neural networks to their full capability. Therefore, tra…
cs.LG2019★ 7 cited
Multi-source Distilling Domain Adaptation
Sicheng Zhao, Guangzhi Wang, Shanghang Zhang +7
Deep neural networks suffer from performance decay when there is domain shift between the labeled source domain and unlabeled target domain, which motivates the research on domain…