Addressing Non-IID with Data Quantity Skew in Federated Learning
Non-IID is one of the key challenges in federated learning. Data heterogeneity may lead to slower convergence, reduced accuracy, and more training rounds. To address the common Non-IID data distribution problem in federated learning, we propose a comprehensive dynamic optimization approach based on...
| Published in: | Information |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-10-01
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| Subjects: | |
| Online Access: | https://www.mdpi.com/2078-2489/16/10/861 |