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GLow - A Novel, Flower-Based Simulated Gossip Learning Strategy
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DOI：10.1016/j.jpdc.2026.105272.png)
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Abstract
En 中文
• Creation of a Decentralized Federated Learning (Gossip Learning) strategy to simulate fully distributed agent configurations. • Deploy and evaluate custom network scenarios and assess how interconnection among agents affect distributed systems convergence. • Experimentation with MNIST and CIFAR10 datasets and 8, 16 network agents to second the viability of the designed Gossip Learning system. • Real-world application in the cybersecurity domain - Network Intrusion Detection Systems.
Keywords:
Distributed systems
Decentralized federated learning
Network topologies
Gossip learning
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4
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3.8K
Citations:
4.8K
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