AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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DeepFedNAS is introduced, a two-phase framework built on a multi-objective fitness function that synthesizes information-theoretic network metrics with architectural heuristics that makes DeepFedNAS practical for scalable, communication-constrained IoT federations.
FEAST is proposed, a federated shared-space training framework that counters this imbalance by jointly training multiple subnetworks within each client's limit by introducing a one-parameter $\gamma$-allocation protocol to control this coupling.
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