FedNKD: A Dependable Federated Learning Using Fine-tuned Random Noise and Knowledge Distillation.
Shaoxiong Zhu|Qi Qi|Zirui Zhuang|Jingyu Wang|Haifeng Sun|Jianxin Liao
| Anthology ID: | DBLP:conf/mir/Zhu0Z0SL22 |
|---|---|
| Volume: | ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27 - 30, 2022 |
| Year: | 2022 |
| Venue: | International Conference on Multimedia Retrieval (ICMR) |
| Publisher: | ACM |
| Pages: | 185-193 |
| URL: | https://doi.org/10.1145/3512527.3531372 |
| DOI: | https://doi.org/10.1145/3512527.3531372 |
| DBLP: | conf/mir/Zhu0Z0SL22 |
| BibTeX: |
@inproceedings{zhu-2022-fednkd,
author = {Shaoxiong Zhu and
Qi Qi and
Zirui Zhuang and
Jingyu Wang and
Haifeng Sun and
Jianxin Liao},
editor = {Vincent Oria and
Maria Luisa Sapino and
Shin'ichi Satoh and
Brigitte Kerherv\'{e} and
Wen-Huang Cheng and
Ichiro Ide and
Vivek K. Singh},
title = {{FedNKD: A Dependable Federated Learning Using Fine-tuned Random Noise and Knowledge Distillation}},
booktitle = {{ICMR '22: International Conference on Multimedia Retrieval, Newark, NJ, USA, June 27 - 30, 2022}},
pages = {185--193},
publisher = {ACM},
year = {2022},
url = {https://doi.org/10.1145/3512527.3531372},
doi = {https://doi.org/10.1145/3512527.3531372}
}