"Enabling Privacy-Preserving and Publicly Auditable Federated Learning."

Huang Zeng et al. (2024)

> Home

Details and statistics

DOI: 10.1109/ICC51166.2024.10622406

access: closed

type: Conference or Workshop Paper

metadata version: 2024-10-06

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/icc/ZengY0CXLY24
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/icc/ZengY0CXLY24
Huang Zeng, Anjia Yang, Jian Weng, Min-Rong Chen, Fengjun Xiao, Yi Liu, Ye Yao:
Enabling Privacy-Preserving and Publicly Auditable Federated Learning. ICC 2024: 5178-5183

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.