CUSNTF: A Scalable Sparse Non-negative Tensor Factorization Model for Large-scale Industrial Applications on Multi-GPU.
Hao Li|Kenli Li|Ji-yao An|Keqin Li
| Anthology ID: | DBLP:conf/cikm/LiLAL18 |
|---|---|
| Volume: | Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018 |
| Year: | 2018 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 1113-1122 |
| URL: | https://doi.org/10.1145/3269206.3271749 |
| DOI: | https://doi.org/10.1145/3269206.3271749 |
| DBLP: | conf/cikm/LiLAL18 |
| BibTeX: |
@inproceedings{li-2018-cusntf,
author = {Hao Li and
Kenli Li and
Ji-yao An and
Keqin Li},
editor = {Alfredo Cuzzocrea and
James Allan and
Norman W. Paton and
Divesh Srivastava and
Rakesh Agrawal and
Andrei Z. Broder and
Mohammed J. Zaki and
K. Sel\c{c}uk Candan and
Alexandros Labrinidis and
Assaf Schuster and
Haixun Wang},
title = {{CUSNTF: A Scalable Sparse Non-negative Tensor Factorization Model for Large-scale Industrial Applications on Multi-GPU}},
booktitle = {{Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018}},
pages = {1113--1122},
publisher = {ACM},
year = {2018},
url = {https://doi.org/10.1145/3269206.3271749},
doi = {https://doi.org/10.1145/3269206.3271749}
}