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math.OC2026
A Complete Characterization of Optimal Subgradient Methods for Lipschitz Convex Minimization
Aaron Zoll, Benjamin Grimmer
We consider the design of optimal fixed-step first-order methods for -Lipschitz convex optimization given . Prior works have identified several distinct f…
math.OC2026
Inexactly Smooth Performance Estimation and New Optimized Gradient Methods
Aaron Zoll, Benjamin Grimmer
We consider a general class of ``inexactly smooth'' convex functions, providing a universal model capturing as special cases -smooth, -Lipschitz, and Hölder smooth functions,…
math.OC2026
A Parameter-Free Restart Scheme with Only a Parallelizable Overhead
Yue Wu, Benjamin Grimmer
It is well-known that first-order methods can offer accelerated convergence rates in the presence of growth structures. Restarting schemes provide a general tool for such speed-ups…