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Zhejiang University
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Adam's complex adaptive behavior boils down to an invariant, heavy-tailed moment ratio that enables zero-overhead 4-bit optimizer compression and formally unifies Adam with sign-based momentum.
AEGIS slashes token recovery rates to nearly zero while preserving model performance, tackling all three critical channels of information leakage in federated learning.
