"PPFL: Privacy-preserving Federated Learning with Trusted Execution ..."

Fan Mo et al. (2021)

> Home

Details and statistics

DOI: —

access: open

type: Informal or Other Publication

metadata version: 2021-05-04

- view
  - electronic edition @ arxiv.org (open access)
- export record
  dblp key:
  - journals/corr/abs-2104-14380
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2104-14380
Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, Nicolas Kourtellis:
PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments. CoRR abs/2104.14380 (2021)

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.