RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback.
Ilya Shenbin|Anton Alekseev|Elena Tutubalina|Valentin Malykh|Sergey I. Nikolenko
| Anthology ID: | DBLP:conf/wsdm/ShenbinATMN20 |
|---|---|
| Volume: | WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020 |
| Year: | 2020 |
| Venue: | Web Search and Data Mining (WSDM) |
| Publisher: | ACM |
| Pages: | 528-536 |
| URL: | https://doi.org/10.1145/3336191.3371831 |
| DOI: | https://doi.org/10.1145/3336191.3371831 |
| DBLP: | conf/wsdm/ShenbinATMN20 |
| BibTeX: |
@inproceedings{shenbin-2020-recvae,
author = {Ilya Shenbin and
Anton Alekseev and
Elena Tutubalina and
Valentin Malykh and
Sergey I. Nikolenko},
editor = {James Caverlee and
Xia Ben Hu and
Mounia Lalmas-Roelleke and
Wei Wang},
title = {{RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback}},
booktitle = {{WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020}},
pages = {528--536},
publisher = {ACM},
year = {2020},
url = {https://doi.org/10.1145/3336191.3371831},
doi = {https://doi.org/10.1145/3336191.3371831}
}