Submitted to Future Generation Computer Systems
FedEnD: Communication-Efficient Federated Learning for Non-IID Data via Decentralized Ensemble Distillation
Quick facts
- Year
- 2026
- Venue
- Submitted to Future Generation Computer Systems
- Identifier
- martinezbeltran2026fedend
Suggested citation
Enrique Tomás Martínez Beltrán, Philip Giryes, Gérôme Bovet, Burkhard Stiller, Gregorio Martínez Pérez, Alberto Huertas Celdrán (2026). FedEnD: Communication-Efficient Federated Learning for Non-IID Data via Decentralized Ensemble Distillation. Submitted to Future Generation Computer Systems.
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Submitted to Information Fusion
Decentralized Self-Supervised Representation Learning via Prototype Exchange under Non-IID Data
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arXiv preprint arXiv:2603.08424
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