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We study preconditioned proximal point methods for a class of saddle point problems, where the preconditioner decouples the overall proximal point method into an alternating primal--dual method. This is akin to the Chambolle--Pock method or…

Optimization and Control · Mathematics 2020-02-13 Tuomo Valkonen

Numerical solution of discrete PDEs corresponding to saddle point problems is highly relevant to physical systems such as Stokes flow. However, scaling up numerical solvers for such systems is often met with challenges in efficiency and…

Numerical Analysis · Mathematics 2024-08-23 Yutian Tao , Eftychios Sifakis

The article is devoted to the development of numerical methods for solving saddle point problems and variational inequalities with simplified requirements for the smoothness conditions of functionals. Recently there were proposed some…

Optimization and Control · Mathematics 2023-11-22 Alexander Titov , Fedor Stonyakin , Mohammad Alkousa , Alexander Gasnikov

The goal of this work is to construct and study hybrid and multiplicative two-level overlapping Schwarz algorithms with standard coarse spaces for the almost incompressible linear elasticity and Stokes systems, discretized by mixed finite…

Numerical Analysis · Mathematics 2016-11-03 Mingchao Cai , Luca F. Pavarino

This paper introduces a preconditioned method designed to comprehensively address the saddle point system with the aim of improving convergence efficiency. In the preprocessor construction phase, a technical approach for solving the…

Numerical Analysis · Mathematics 2024-04-10 Juan Zhang , Yiyi Luo

We propose a doubly stochastic primal-dual coordinate optimization algorithm for empirical risk minimization, which can be formulated as a bilinear saddle-point problem. In each iteration, our method randomly samples a block of coordinates…

Machine Learning · Computer Science 2017-04-13 Adams Wei Yu , Qihang Lin , Tianbao Yang

Based on the needs of convergence proofs of preconditioned proximal point methods, we introduce notions of partial strong submonotonicity and partial (metric) subregularity of set-valued maps. We study relationships between these two…

Optimization and Control · Mathematics 2020-03-02 Tuomo Valkonen

In this paper, a class of new preconditioners based on matrix splitting are presented for generalized saddle-point linear systems, which can be viewed as further modified improvements of some recently published preconditioners. Moreover, we…

Numerical Analysis · Mathematics 2018-10-02 Zhao-Zheng Liang , Guo-Feng Zhang

We have presented a fast method for solving a specific type of block four-by-four saddlepoint problem arising from the finite element discretization of the generalized 3D Stokes problem. We analyze the eigenvalue distribution and the…

Numerical Analysis · Mathematics 2024-02-22 Achraf Badahmane , Ahmed Ratnani , Hassane Sadok

In this paper, we execute the shift-splitting preconditioner for asymmetric saddle point problems with its (1,2) block's transposition unequal to its (2,1) block under the removed minus of its (2,1) block. The proposed preconditioner is…

Numerical Analysis · Mathematics 2021-09-13 Shi-Liang Wu , Davod Khojasteh Salkuyeh

We consider systems of nonlinear magnetostatics and quasistatics that typically arise in the modeling and simulation of electric machines. The nonlinear problems, eventually obtained after time discretization, are usually solved by…

Numerical Analysis · Mathematics 2023-11-27 Herbert Egger , Felix Engertsberger , Bogdan Radu

We consider the solution of saddle-point systems with a tree-based block structure, introducing a parallelizable direct method for their solution. As our key contribution, we then propose several structure-exploiting preconditioners to be…

Numerical Analysis · Mathematics 2024-11-01 Christoph Hansknecht , Bernhard Heinzelreiter , John W. Pearson , Andreas Potschka

This paper concerns robust numerical treatment of an elliptic PDE with high contrast coefficients, for which classical finite-element discretizations yield ill-conditioned linear systems. This paper introduces a procedure by which the…

Numerical Analysis · Mathematics 2018-08-03 Yuliya Gorb , Vasiliy Kramarenko , Yuri Kuznetsov

Monotone inclusions have a wide range of applications, including minimization, saddle-point, and equilibria problems. We introduce new stochastic algorithms, with or without variance reduction, to estimate a root of the expectation of…

Optimization and Control · Mathematics 2024-05-24 Abdurakhmon Sadiev , Laurent Condat , Peter Richtárik

In this paper, we introduce some adaptive methods for solving variational inequalities with relatively strongly monotone operators. Firstly, we focus on the modification of the recently proposed, in smooth case [1], adaptive numerical…

Optimization and Control · Mathematics 2022-11-01 A. A. Titov , S. S. Ablaev , M. S. Alkousa , F. S. Stonyakin , A. V. Gasnikov

Compatible finite element discretisations for the atmospheric equations of motion have recently attracted considerable interest. Semi-implicit timestepping methods require the repeated solution of a large saddle-point system of linear…

We investigate the convergence properties of a stochastic primal-dual splitting algorithm for solving structured monotone inclusions involving the sum of a cocoercive operator and a composite monotone operator. The proposed method is the…

Optimization and Control · Mathematics 2016-02-26 Lorenzo Rosasco , Silvia Villa , Bang Cong Vu

We consider the problem of iteratively solving large and sparse double saddle-point systems arising from the stationary Stokes-Darcy equations in two dimensions, discretized by the Marker-and-Cell (MAC) finite difference method. We analyze…

Numerical Analysis · Mathematics 2023-02-28 Chen Greif , Yunhui He

We present a non-conforming least squares method for approximating solutions of second order elliptic problems with discontinuous coefficients. The method is based on a general Saddle Point Least Squares (SPLS) method introduced in previous…

Numerical Analysis · Mathematics 2019-04-01 Constantin Bacuta , Jacob Jacavage

This paper is a survey of methods for solving smooth (strongly) monotone stochastic variational inequalities. To begin with, we give the deterministic foundation from which the stochastic methods eventually evolved. Then we review methods…

Optimization and Control · Mathematics 2023-04-04 Aleksandr Beznosikov , Boris Polyak , Eduard Gorbunov , Dmitry Kovalev , Alexander Gasnikov