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cs.DC2025
Clustered Federated Learning with Hierarchical Knowledge Distillation
Sabtain Ahmad, Meerzhan Kanatbekova, Ivona Brandic +1
Clustered Federated Learning (CFL) has emerged as a powerful approach for addressing data heterogeneity and ensuring privacy in large distributed IoT environments. By clustering cl…
cs.NE2025
From Silicon to Spikes: System-Wide Efficiency Gains via Exact Event-Driven Training in Neuromorphic Computing
Arman Ferdowsi, Atakan Aral
Spiking neural networks (SNNs) promise orders-of-magnitude efficiency gains by communicating with sparse, event-driven spikes rather than dense numerical activations. However, most…