A. Passalacqua

On the robustness of noisy solutions in non-convex neural networks

Using a finite energy message-passing algorithm, it is demonstrated numerically that thermal noise enables effective generalization in the regime of constraint densities where both recovering the teacher and finding a zero temperature solution are computationally hard.