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Shallow Probes Are Sufficient for Near-Oracle Personalization Depth Allocation in Federated Learning
Rather than proposing a new federated optimizer, we study whether a small client-specific measurement budget can support cost-aware personalization-depth decisions under a utility that trades Macro-F1 against deployment cost. Exhaustive evaluation of six depths defines an offline oracle that is not
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