Resolvent splitting for sums of monotone operators with minimal lifting
@article{Malitsky2021ResolventSF, title={Resolvent splitting for sums of monotone operators with minimal lifting}, author={Yura Malitsky and Matthew K. Tam}, journal={Mathematical Programming}, year={2021} }
In this work, we study fixed point algorithms for finding a zero in the sum of n ≥ 2 maximally monotone operators by using their resolvents. More precisely, we consider the class of such algorithms where each resolvent is evaluated only once per iteration. For any algorithm from this class, we show that the underlying fixed point operator is necessarily defined on a d -fold Cartesian product space with d ≥ n − 1. Further, we show that this bound is unimprovable by providing a family of examples for…
12 Citations
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References
SHOWING 1-10 OF 26 REFERENCES
A primal-dual splitting algorithm for composite monotone inclusions with minimal lifting
- Mathematics, Computer ScienceNumerical Algorithms
- 2022
This work establishes the first primal-dual splitting algorithm for composite monotone inclusions with minimal lifting, which reduces the dimension of the product space where the underlying fixed point operator is defined, in comparison to other algorithms, without requiring additional evaluations of the resolvent operators.
On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators
- Computer Science, MathematicsMath. Program.
- 1992
This paper shows, by means of an operator called asplitting operator, that the Douglas—Rachford splitting method for finding a zero of the sum of two monotone operators is a special case of the proximal point algorithm, which allows the unification and generalization of a variety of convex programming algorithms.
A product space reformulation with reduced dimension for splitting algorithms
- MathematicsComputational Optimization and Applications
- 2022
In this paper we propose a product space reformulation to transform monotone inclusions described by finitely many operators on a Hilbert space into equivalent two-operator problems. Our approach…
Strengthened splitting methods for computing resolvents
- Computer Science, MathematicsComputational Optimization and Applications
- 2021
A systematic framework for computing the resolvent of the sum of two or more monotone operators which only activates each operator in the sum individually, which can be viewed as a type of regularisation that preserves computational tractability.
Iteration-Complexity of Block-Decomposition Algorithms and the Alternating Direction Method of Multipliers
- Mathematics, Computer ScienceSIAM J. Optim.
- 2013
A framework of block-decomposition prox-type algorithms for solving the monotone inclusion problem and shows that any method in this framework is also a special instance of the hybrid proximal extragradient (HPE) method introduced by Solodov and Svaiter is shown.
Proximal Splitting Algorithms for Convex Optimization: A Tour of Recent Advances, with New Twists
- Computer Science
- 2019
This overview of recent proximal splitting algorithms presents them within a unified framework, which consists in applying splitting methods for monotone inclusions in primal-dual product spaces, with well-chosen metrics, and emphasizes that when the smooth term in the objective function is quadratic, convergence is guaranteed with larger values of the relaxation parameter than previously known.
Monotone Operators and the Proximal Point Algorithm
- Mathematics
- 1976
For the problem of minimizing a lower semicontinuous proper convex function f on a Hilbert space, the proximal point algorithm in exact form generates a sequence $\{ z^k \} $ by taking $z^{k + 1} $…
Uniqueness of DRS as the 2 operator resolvent-splitting and impossibility of 3 operator resolvent-splitting
- MathematicsMath. Program.
- 2020
This work presents the answer by providing a novel 3 operator resolvent-splitting with provably minimal lifting that directly generalizes DRS.
A Primal–Dual Splitting Method for Convex Optimization Involving Lipschitzian, Proximable and Linear Composite Terms
- Mathematics, Computer ScienceJ. Optim. Theory Appl.
- 2013
This work brings together and notably extends several classical splitting schemes, like the forward–backward and Douglas–Rachford methods, as well as the recent primal–dual method of Chambolle and Pock designed for problems with linear composite terms.
Line search for averaged operator iteration
- Computer Science2016 IEEE 55th Conference on Decision and Control (CDC)
- 2016
This paper proposes a line search for averaged iteration that preserves the theoretical convergence guarantee, while often accelerating practical convergence, in first order algorithms for convex optimization.