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cs.LG2026
Cumulative Utility Parity for Fair Federated Learning under Intermittent Client Participation
Stefan Behfar, Richard Mortier
In real-world federated learning (FL) systems, client participation is intermittent, heterogeneous, and often correlated with data characteristics or resource constraints. Existing…
cs.LG2023
Analysis of Information Propagation in Ethereum Network Using Combined Graph Attention Network and Reinforcement Learning to Optimize Network Efficiency and Scalability
Stefan Kambiz Behfar, Jon Crowcroft
Blockchain technology has revolutionized the way information is propagated in decentralized networks. Ethereum plays a pivotal role in facilitating smart contracts and decentralize…
cs.LG2023
Probabilistic Sampling-Enhanced Temporal-Spatial GCN: A Scalable Framework for Transaction Anomaly Detection in Ethereum Networks
Stefan Kambiz Behfar, Jon Crowcroft
The rapid evolution of the Ethereum network necessitates sophisticated techniques to ensure its robustness against potential threats and to maintain transparency. While Graph Neura…