3 papers
math.OC2026
Sharp Dimension Dependence for the Last Iterate of the SubGradient Method
Guglielmo Beretta, Tommaso Cesari, Roberto Colomboni +1
We study the last iterate of the projected subGradient Method (sGM) for convex Lipschitz objectives defined on . We prove that, for a finite horizon and a constan…
math.OC2026
New Bounds for the Last Iterate of the Stochastic subGradient Method
Guglielmo Beretta, Tommaso Cesari, Roberto Colomboni +1
We study the last iterate of the stochastic subgradient method for one-dimensional convex Lipschitz objectives. For a fixed horizon , we consider the standard fixed stepsizes $Î…
math.OC2025
An Improved Analysis of the Clipped Stochastic subGradient Method under Heavy-Tailed Noise
Daniela Angela Parletta, Andrea Paudice, Saverio Salzo
In this paper, we provide novel optimal (or near optimal) convergence rates for a clipped version of the stochastic subgradient method. We consider nonsmooth convex problems over p…