This paper proposes an accelerated proximal point method for maximally monotone operators. The proof is computer-assisted via the performance estimation problem approach. The proximal point method includes various well-known convex optimization methods, such as the proximal method of multipliers and the alternating direction method of multipliers, and thus the proposed acceleration has wide applications. Numerical experiments are presented to demonstrate the accelerating behaviors.
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CITATION STYLE
Kim, D. (2021). Accelerated proximal point method for maximally monotone operators. Mathematical Programming, 190(1–2), 57–87. https://doi.org/10.1007/s10107-021-01643-0