Federated Learning Based on Diffusion Model to Cope with Non-IID Data

Zhuang Zhao, Feng Yang, Guirong Liang. Federated Learning Based on Diffusion Model to Cope with Non-IID Data. In Qingshan Liu 0001, Hanzi Wang, Zhanyu Ma, Weishi Zheng 0001, Hongbin Zha, Xilin Chen 0001, Liang Wang, Rongrong Ji, editors, Pattern Recognition and Computer Vision - 6th Chinese Conference, PRCV 2023, Xiamen, China, October 13-15, 2023, Proceedings, Part IX. Volume 14433 of Lecture Notes in Computer Science, pages 220-231, Springer, 2023. [doi]

@inproceedings{ZhaoYL23-3,
  title = {Federated Learning Based on Diffusion Model to Cope with Non-IID Data},
  author = {Zhuang Zhao and Feng Yang and Guirong Liang},
  year = {2023},
  doi = {10.1007/978-981-99-8546-3_18},
  url = {https://doi.org/10.1007/978-981-99-8546-3_18},
  researchr = {https://researchr.org/publication/ZhaoYL23-3},
  cites = {0},
  citedby = {0},
  pages = {220-231},
  booktitle = {Pattern Recognition and Computer Vision - 6th Chinese Conference, PRCV 2023, Xiamen, China, October 13-15, 2023, Proceedings, Part IX},
  editor = {Qingshan Liu 0001 and Hanzi Wang and Zhanyu Ma and Weishi Zheng 0001 and Hongbin Zha and Xilin Chen 0001 and Liang Wang and Rongrong Ji},
  volume = {14433},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-981-99-8546-3},
}