researcher

Wei Wang

Dalian University of Technology-Ritsumeikan University (DUT-RU) International School of Information Science & Engineering, Dalian University of Technology

9 papers hereh-index 15702 citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position

first author2
middle author3
last author3

Across the 8 of 9 papers where every author was matched, so the position is known.

fields

affiliations

Dalian University of Technology-Ritsumeikan University (DUT-RU) International School of Information Science & Engineering, Dalian University of Technology

Homepage

same name

Wei Wang — 349 papers
Wei Wang — 102 papers, h 34
Wei Wang — 63 papers, h 53
Wei Wang — 43 papers, h 8
Wei Wang — 36 papers, h 14
Wei Wang — 35 papers, h 55

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity

20202022

most citedRethink Maximum Mean Discrepancy for Domain Adaptation

19 citations · 52 across the 9 of their papers we have counts for

collaborators

Showing 2020Show all

3 papers · 1 filter

cs.LG2020★ 3 cited

Improving Unsupervised Domain Adaptation by Reducing Bi-level Feature Redundancy

Mengzhu Wang, Xiang Zhang, Long Lan +3

Reducing feature redundancy has shown beneficial effects for improving the accuracy of deep learning models, thus it is also indispensable for the models of unsupervised domain ada…

cs.LG2020★ 19 cited

Rethink Maximum Mean Discrepancy for Domain Adaptation

Wei Wang, Haojie Li, Zhengming Ding +1

Existing domain adaptation methods aim to reduce the distributional difference between the source and target domains and respect their specific discriminative information, by estab…

cs.CV2020★ 1 cited

Sparsely-Labeled Source Assisted Domain Adaptation

Wei Wang, Zhihui Wang, Yuankai Xiang +4

Domain Adaptation (DA) aims to generalize the classifier learned from the source domain to the target domain. Existing DA methods usually assume that rich labels could be available…