67 citations · 158 across the 17 of their papers we have counts for
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cs.LG2021★ 7 cited
Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li +3
Multi-source domain adaptation aims at leveraging the knowledge from multiple tasks for predicting a related target domain. Hence, a crucial aspect is to properly combine different…
cs.LG2021★ 4 cited
On the benefits of representation regularization in invariance based domain generalization
Changjian Shui, Boyu Wang, Christian Gagné
A crucial aspect in reliable machine learning is to design a deployable system in generalizing new related but unobserved environments. Domain generalization aims to alleviate such…
cs.LG2021★ 2 cited
Multi-task Learning by Leveraging the Semantic Information
Fan Zhou, Brahim Chaib-draa, Boyu Wang
One crucial objective of multi-task learning is to align distributions across tasks so that the information between them can be transferred and shared. However, existing approaches…