Scalpel-CD: Leveraging Crowdsourcing and Deep Probabilistic Modeling for Debugging Noisy Training Data.
Jie Yang|Alisa Smirnova|Dingqi Yang|Gianluca Demartini|Yuan Lu|Philippe Cudré-Mauroux
| Anthology ID: | DBLP:conf/www/YangSYDLC19 |
|---|---|
| Volume: | The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 |
| Year: | 2019 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 2158-2168 |
| URL: | https://doi.org/10.1145/3308558.3313599 |
| DOI: | https://doi.org/10.1145/3308558.3313599 |
| DBLP: | conf/www/YangSYDLC19 |
| BibTeX: |
@inproceedings{yang-2019-scalpelcd,
author = {Jie Yang and
Alisa Smirnova and
Dingqi Yang and
Gianluca Demartini and
Yuan Lu and
Philippe Cudr\'{e}-Mauroux},
editor = {Ling Liu and
Ryen W. White and
Amin Mantrach and
Fabrizio Silvestri and
Julian J. McAuley and
Ricardo Baeza-Yates and
Leila Zia},
title = {{Scalpel-CD: Leveraging Crowdsourcing and Deep Probabilistic Modeling for Debugging Noisy Training Data}},
booktitle = {{The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019}},
pages = {2158--2168},
publisher = {ACM},
year = {2019},
url = {https://doi.org/10.1145/3308558.3313599},
doi = {https://doi.org/10.1145/3308558.3313599}
}