The codes of Bootstrapping Informative Graph Augmentation via A Meta Learning Approach
train model: python3 ./MEGA_train.py --dataset IMDB-MULTI --batch_size 64 --emb_dim 64 --reg_expect 0.4 --pooling_type layerwise
If you find the codes useful, please cite:
@inproceedings{DBLP:conf/ijcai/GaoLQS0Z22, author = {Hang Gao and Jiangmeng Li and Wenwen Qiang and Lingyu Si and Fuchun Sun and Changwen Zheng}, editor = {Luc De Raedt}, title = {Bootstrapping Informative Graph Augmentation via {A} Meta Learning Approach}, booktitle = {Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, {IJCAI} 2022, Vienna, Austria, 23-29 July 2022}, pages = {3001--3007}, publisher = {ijcai.org}, year = {2022}, url = {https://doi.org/10.24963/ijcai.2022/416}, doi = {10.24963/ijcai.2022/416}, timestamp = {Wed, 27 Jul 2022 16:43:00 +0200}, biburl = {https://dblp.org/rec/conf/ijcai/GaoLQS0Z22.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }