Author

E. Naldi

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Preprint Jul 2026

Langevin for Nonconvex Optimization: Exact, Inexact and Zeroth-Order

We study Langevin-based methods for non-convex optimization under smoothness and dissipativity assumptions. Our focus is on obtaining non-asymptotic bounds for the expected excess risk rather than sampling guarantees for the full target distribution. The key ingredient of our analysis is a direct passage from relative...

E. Naldi, Marco Rando, Lorenzo Rosasco et al. · 0 citations