When input perturbation outperforms gradient perturbation: Achieving high-accuracy deep learning under local differential privacy.
Shunshun Peng|Jun Zhang|Chenxing Hu|Quanwang Wu|Hongbing Wang|Mengmeng Yang|Taolin Guo
| Anthology ID: | DBLP:journals/ipm/PengZHWWYG26 |
|---|---|
| Year: | 2026 |
| Venue: | Information Processing and Management |
| Pages: | 104879 |
| URL: | https://doi.org/10.1016/J.IPM.2026.104879 |
| DOI: | https://doi.org/10.1016/J.IPM.2026.104879 |
| DBLP: | journals/ipm/PengZHWWYG26 |
| BibTeX: |
@article{peng-2026-input,
author = {Shunshun Peng and
Jun Zhang and
Chenxing Hu and
Quanwang Wu and
Hongbing Wang and
Mengmeng Yang and
Taolin Guo},
title = {{When input perturbation outperforms gradient perturbation: Achieving high-accuracy deep learning under local differential privacy}},
journal = {Information Processing and Management},
volume = {63},
number = {7},
pages = {104879},
year = {2026},
url = {https://doi.org/10.1016/J.IPM.2026.104879},
doi = {https://doi.org/10.1016/J.IPM.2026.104879}
}