Towards practical federated unlearning: A knowledge distillation solution
Federated learning(FL) enables collaborative model training without sharing raw data, yet faces a growing challenge: efficiently removing the influence of a specific client’s data to comply with privacy regulations such as the “right to be forgotten.” In this paper, we introduce a novel knowledge di...
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| Main Authors: | , , , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
Elsevier
2026-06-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016826002164 |
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