DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization.

Zheqi Lv|Wenqiao Zhang|Shengyu Zhang|Kun Kuang|Feng Wang|Yongwei Wang|Zhengyu Chen|Tao Shen|Hongxia Yang|Beng Chin Ooi|Fei Wu


Anthology ID:DBLP:conf/www/LvZ0KWW0SYO023
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:3077-3085
URL:https://doi.org/10.1145/3543507.3583451
DOI:https://doi.org/10.1145/3543507.3583451
DBLP:conf/www/LvZ0KWW0SYO023
BibTeX:
@inproceedings{lv-2023-duet, author = {Zheqi Lv and Wenqiao Zhang and Shengyu Zhang and Kun Kuang and Feng Wang and Yongwei Wang and Zhengyu Chen and Tao Shen and Hongxia Yang and Beng Chin Ooi and Fei Wu}, editor = {Ying Ding and Jie Tang and Juan F. Sequeda and Lora Aroyo and Carlos Castillo and Geert-Jan Houben}, title = {{DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization}}, booktitle = {{Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 - 4 May 2023}}, pages = {3077--3085}, publisher = {ACM}, year = {2023}, url = {https://doi.org/10.1145/3543507.3583451}, doi = {https://doi.org/10.1145/3543507.3583451} }