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Yitzchak Shmalo

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Preprint Jul 2026

A law of robustness for two-layer neural networks with arbitrary weights

A universal version of this law for Lipschitz-parameterized classes is proved, but under a polynomial bound on the parameters; at depth three that boundedness hypothesis is genuinely necessary.

Yitzchak Shmalo · 0 citations