Communication-Balancing Threshold for Event-Triggered Federated Learning

Federated Learning (FL) enables training models across distributed devices while preserving data privacy by avoiding raw data sharing. However, it suffers from significant communication overhead. Event-Triggered FL (ETFL) addresses this issue by allowing devices to transmit updates only when substan...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:IEEE Access
المؤلفون الرئيسيون: Juhyeong Yoon, Jun-Pyo Hong, Jaeyoung Song
التنسيق: مقال
اللغة:الإنجليزية
منشور في: IEEE 2025-01-01
الموضوعات:
Federated learning
event-triggered federated learning
decentralized federated learning
event-triggering threshold
الوصول للمادة أونلاين:https://ieeexplore.ieee.org/document/11096591/

الانترنت

https://ieeexplore.ieee.org/document/11096591/

مواد مشابهة