EdgeMove: Pipelining Device-Edge Model Training for Mobile Intelligence.
Zeqian Dong|Qiang He|Feifei Chen|Hai Jin|Tao Gu|Yun Yang
| Anthology ID: | DBLP:conf/www/Dong00JG023 |
|---|---|
| Volume: | Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023 |
| Year: | 2023 |
| Venue: | The Web Conference (WWW) |
| Publisher: | ACM |
| Pages: | 3142-3153 |
| URL: | https://doi.org/10.1145/3543507.3583540 |
| DOI: | https://doi.org/10.1145/3543507.3583540 |
| DBLP: | conf/www/Dong00JG023 |
| BibTeX: |
@inproceedings{dong-2023-edgemove,
author = {Zeqian Dong and
Qiang He and
Feifei Chen and
Hai Jin and
Tao Gu and
Yun Yang},
editor = {Ying Ding and
Jie Tang and
Juan F. Sequeda and
Lora Aroyo and
Carlos Castillo and
Geert-Jan Houben},
title = {{EdgeMove: Pipelining Device-Edge Model Training for Mobile Intelligence}},
booktitle = {{Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}},
pages = {3142--3153},
publisher = {ACM},
year = {2023},
url = {https://doi.org/10.1145/3543507.3583540},
doi = {https://doi.org/10.1145/3543507.3583540}
}