Penalty-Based Smoothing and Accelerated Inertial Dynamics for Convex Supremum Optimization

We study dual-penalty smoothing for convex functions with a finite-dimensional supremum representation. The regularization yields a differentiable surrogate with controlled approximation error, a single-valued dual maximizer, and explicit gradient formulas. We then study an accelerated inertial dyna