AINeutralarXiv – CS AI · 18h ago5/10
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HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning
Researchers propose HASA, a subnet allocation algorithm for federated learning that assigns model sizes to edge devices based on data heterogeneity rather than just compute constraints. The method improves prediction accuracy across distributed clients while maintaining fixed computational budgets, with implications for efficient on-device AI deployment.