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Previous domain adaptation methods use a discriminator is classifify different domains (as categorical values), while GRDA's discriminator directly reconstructs the domain graph (as a adjacency matrix). -
Previous domain adaptation methods' encoders ignore domain IDs, while GRDA takes the domain IDs with the domain graph as input.
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Traditional DA is equivalent to using our GRDA with a fully-connected graph (i.e., a clique). -
D and E converge if and only if 𝔼 i~p(u|e),j~p(u|e') [A i,j |e, e'] = 𝔼 i,j [A i,j ]. -
The global optimum of the two-player game between E and D matches the three-player game between E, D, and F.
pip install -r requirements.txt
python main.py
python -m visdom.server -p 2000
@inproceedings { GRDA , title = { Graph-Relational Domain Adaptation } , author = { Xu, Zihao and He, Hao and Lee, Guang-He and Wang, Yuyang and Wang, Hao } , booktitle = { International Conference on Learning Representations } , year = { two thousand and twenty-two } }