PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds

Cite

Text

Zhu et al. "PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds." International Joint Conference on Artificial Intelligence, 2024.

Markdown

[Zhu et al. "PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds." International Joint Conference on Artificial Intelligence, 2024.](https://mlanthology.org/ijcai/2024/zhu2024ijcai-privsgp/)

BibTeX

@inproceedings{zhu2024ijcai-privsgp,
  title     = {{PrivSGP-VR: Differentially Private Variance-Reduced Stochastic Gradient Push with Tight Utility Bounds}},
  author    = {Zhu, Zehan and Huang, Yan and Wang, Xin and Xu, Jinming},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2024},
  pages     = {5743-5752},
  url       = {https://mlanthology.org/ijcai/2024/zhu2024ijcai-privsgp/}
}