FedEasy : Federated learning with ease
Federated learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data while preserving privacy and adhering to regulations. However, existing FL frameworks often require extensive code modifications, creating challenges for researchers. In this paper, w...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711025002432 |
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