"Prototype-based fine-tuning for mitigating data heterogeneity in federated ..."

Liming Chai, Jun Xie, Nanrun Zhou (2025)

> Home

Details and statistics

DOI: 10.1016/J.FUTURE.2025.107831

access: closed

type: Journal Article

metadata version: 2025-05-09

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/fgcs/ChaiXZ25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/fgcs/ChaiXZ25
Liming Chai, Jun Xie, Nanrun Zhou:
Prototype-based fine-tuning for mitigating data heterogeneity in federated learning. Future Gener. Comput. Syst. 170: 107831 (2025)

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.