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A Sharper Theory of Ball-Proximal Optimization: Convergence and Radius Selection
We study the exact Euclidean ball-proximal point method for proper, closed, convex functions, where each iteration minimizes the objective over a ball centered at the current point. Retaining the objective gap in the decrease of squared distance yields sharper bounds on objective values, stationarit
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