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#machine learning Preprint Sep 2026

When Does Scale-Invariant Optimization Become Unstable? An Exact Schedule Law with Weight Decay

Normalization renders large parts of neural networks effectively scale invariant, inducing a hidden feedback loop in which learning-rate schedules and weight decay interact through the parameter norm to control the effective step taken by the optimizer. We show that this interaction is governed by an exact discrete-tim...

H. Amin, Wei-Kai Chang, Rajiv Khanna · 0 citations

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