Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective.
Lun Du|Xu Chen|Fei Gao|Qiang Fu|Kunqing Xie|Shi Han|Dongmei Zhang
| Anthology ID: | DBLP:conf/wsdm/DuCGFXHZ22 |
|---|---|
| Volume: | WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022 |
| Year: | 2022 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 230-240 |
| URL: | https://doi.org/10.1145/3488560.3498474 |
| DOI: | https://doi.org/10.1145/3488560.3498474 |
| DBLP: | conf/wsdm/DuCGFXHZ22 |
| BibTeX: |
@inproceedings{du-2022-understanding,
author = {Lun Du and
Xu Chen and
Fei Gao and
Qiang Fu and
Kunqing Xie and
Shi Han and
Dongmei Zhang},
editor = {K. Sel\c{c}uk Candan and
Huan Liu and
Leman Akoglu and
Xin Dong and
Jiliang Tang},
title = {{Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective}},
booktitle = {{WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022}},
pages = {230--240},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3488560.3498474},
doi = {https://doi.org/10.1145/3488560.3498474}
}