Accelerated proximal point method for maximally monotone operators

52Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

References Powered by Scopus

A fast iterative shrinkage-thresholding algorithm for linear inverse problems

9555Citations
N/AReaders
Get full text

A first-order primal-dual algorithm for convex problems with applications to imaging

3392Citations
N/AReaders
Get full text

MONOTONE OPERATORS AND THE PROXIMAL POINT ALGORITHM.

2996Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists

41Citations
N/AReaders
Get full text

Convergence results of two-step inertial proximal point algorithm

27Citations
N/AReaders
Get full text

Fast optimization via inertial dynamics with closed-loop damping

13Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

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

Readers over time

‘21‘22‘2402468

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

80%

Researcher 1

20%

Readers' Discipline

Tooltip

Mathematics 2

40%

Decision Sciences 1

20%

Computer Science 1

20%

Engineering 1

20%

Save time finding and organizing research with Mendeley

Sign up for free
0