Information Fusion
Decentralized Federated Learning with Multimodal Prototypes for Heterogeneous Data
Quick facts
- Year
- 2026
- Venue
- Information Fusion
- Identifier
- martinezbeltran2026decentralized
Suggested citation
Enrique Tomás Martínez Beltrán, Gérôme Bovet, Gregorio Martínez Pérez, Alberto Huertas Celdrán (2026). Decentralized Federated Learning with Multimodal Prototypes for Heterogeneous Data. Information Fusion.
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Asynchronous Cache-based Aggregation with Fairness and Filtering for Decentralized Federated Learning
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Decentralized Federated Learning (DFL) offers a scalable paradigm for collaborative intelligence at the edge, yet its practical efficacy is severely constrained by system heterogeneity. Traditional synchronous protocols...
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Decentralized Federated Learning (DFL) enables nodes to collaboratively train models without a central server, introducing new vulnerabilities since each node independently selects peers for model aggregation. Malicious...
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