SPATL-XLC: An Explainability-Driven Framework for Efficient and Robust Federated Learning Under Non-IID Data
Federated learning (FL) enables multiple devices to collectively train a machine learning model without sharing private data. However, when data across devices differ significantly (non-IID),training becomes less accurate and difficult to understand in terms of how the model makes decisions (explain...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11082156/ |
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