"FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving ..."

Weizhao Jin et al. (2023)

> Home

Details and statistics

DOI: 10.48550/ARXIV.2303.10837

access: open

type: Informal or Other Publication

metadata version: 2024-08-04

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/corr/abs-2303-10837
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2303-10837
Weizhao Jin, Yuhang Yao, Shanshan Han, Carlee Joe-Wong, Srivatsan Ravi, Salman Avestimehr, Chaoyang He:
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System. CoRR abs/2303.10837 (2023)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.