arrow
Return

FedLoop: Personalized Federated Learning with Closed-Loop Feature Rectification

delete2026-09-15
delete0
PRE
AI
Z
Zhaoyang Ma
吴
吴志昊 (Zhihao Wu)
X
Xin Gao
L
Lu Wang
Y
Youfang Lin
J
Jing Wang *
L
Lipo Wang *
DOI:10.1016/j.inffus.2026.104785delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
• FedLoop shifts pFL to dynamic, instance-wise feature rectification. • Feedback loop decouples feature rectification into direction and magnitude. • FedLoop achieves SOTA accuracy across modalities with negligible overhead.
Keywords:
Personalized Federated Learning
Closed-Loop
Feature Rectification
Non-IID

Journal

Information Fusion cover
Information Fusion
IF:
15.5
Papers:
4.2K
Citations:
2.7W

Organization

B
Beijing Jiaotong University
Scholars:
2.2W
Papers: 1.7W
Citations: 1.2W
T
tsinghua university
Scholars:
11.9W
Papers: 10.0W
Citations: 137
N
Nanyang Technological University
Scholars:
4.9W
Papers: 4.8W
Citations: 8.1W
researcher View more organizations
Cited Papers

Cited Papers

No cited papers available