Sparsemax and Relaxed Wasserstein for Topic Sparsity.
| Anthology ID: | DBLP:conf/wsdm/LinHG19 |
|---|---|
| Volume: | Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, VIC, Australia, February 11-15, 2019 |
| Year: | 2019 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 141-149 |
| URL: | https://doi.org/10.1145/3289600.3290957 |
| DOI: | https://doi.org/10.1145/3289600.3290957 |
| DBLP: | conf/wsdm/LinHG19 |
| BibTeX: |
@inproceedings{lin-2019-sparsemax,
author = {Tianyi Lin and
Zhiyue Hu and
Xin Guo},
editor = {J. Shane Culpepper and
Alistair Moffat and
Paul N. Bennett and
Kristina Lerman},
title = {{Sparsemax and Relaxed Wasserstein for Topic Sparsity}},
booktitle = {{Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, VIC, Australia, February 11-15, 2019}},
pages = {141--149},
publisher = {ACM},
year = {2019},
url = {https://doi.org/10.1145/3289600.3290957},
doi = {https://doi.org/10.1145/3289600.3290957}
}