arxivcs.LGmath.PRstat.ML2026-07-08
A law of robustness for two-layer neural networks with arbitrary weights
Bubeck, Li and Nagaraj conjectured that, for generic data, any two-layer neural network with $m$ neurons that fits $n$ noisy labels must have Lipschitz constant at least of order $\sqrt{n/m}$, with no restriction on the size of the weights. Bubeck and Sellke proved a universal ve…