SafeML: A Privacy-Preserving Byzantine-Robust Framework for Distributed Machine Learning Training

Meghdad Mirabi, René Klaus Nikiel, Carsten Binnig. SafeML: A Privacy-Preserving Byzantine-Robust Framework for Distributed Machine Learning Training. In Jihe Wang, Yi He 0007, Thang N. Dinh, Christan Grant, Meikang Qiu, Witold Pedrycz, editors, IEEE International Conference on Data Mining, ICDM 2023 - Workshops, Shanghai, China, December 4, 2023. pages 207-216, IEEE, 2023. [doi]

@inproceedings{MirabiNB23,
  title = {SafeML: A Privacy-Preserving Byzantine-Robust Framework for Distributed Machine Learning Training},
  author = {Meghdad Mirabi and René Klaus Nikiel and Carsten Binnig},
  year = {2023},
  doi = {10.1109/ICDMW60847.2023.00033},
  url = {https://doi.org/10.1109/ICDMW60847.2023.00033},
  researchr = {https://researchr.org/publication/MirabiNB23},
  cites = {0},
  citedby = {0},
  pages = {207-216},
  booktitle = {IEEE International Conference on Data Mining, ICDM 2023 - Workshops, Shanghai, China, December 4, 2023},
  editor = {Jihe Wang and Yi He 0007 and Thang N. Dinh and Christan Grant and Meikang Qiu and Witold Pedrycz},
  publisher = {IEEE},
  isbn = {979-8-3503-8164-1},
}