Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng 0005, Yinglong Xia, Charu C. Aggarwal. Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. In Ankur Teredesai, Vipin Kumar, Ying Li, Rómer Rosales, Evimaria Terzi, George Karypis, editors, Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019. pages 1418-1428, ACM, 2019. [doi]
@inproceedings{WuYZXZPXA19,
title = {Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding},
author = {Lingfei Wu and Ian En-Hsu Yen and Zhen Zhang and Kun Xu and Liang Zhao and Xi Peng 0005 and Yinglong Xia and Charu C. Aggarwal},
year = {2019},
doi = {10.1145/3292500.3330918},
url = {https://doi.org/10.1145/3292500.3330918},
researchr = {https://researchr.org/publication/WuYZXZPXA19},
cites = {0},
citedby = {0},
pages = {1418-1428},
booktitle = {Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019, Anchorage, AK, USA, August 4-8, 2019},
editor = {Ankur Teredesai and Vipin Kumar and Ying Li and Rómer Rosales and Evimaria Terzi and George Karypis},
publisher = {ACM},
isbn = {978-1-4503-6201-6},
}