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We propose a modification of the standard linear implicit Euler integrator for the weak approximation of parabolic semilinear stochastic PDEs driven by additive space-time white noise. The new method can easily be combined with a finite…

Numerical Analysis · Mathematics 2022-03-22 Charles-Edouard Bréhier

We consider a bilevel program involving a linear lower level problem with left-hand-side perturbation. We then consider the Karush-Kuhn-Tucker reformulation of the problem and subsequently build a tractable optimization problem with linear…

Optimization and Control · Mathematics 2020-10-23 Floriane Mefo Kue , Thorsten Raasch , Alain B. Zemkoho

With the emergence of mixed precision capabilities in hardware, iterative refinement schemes for solving linear systems $Ax=b$ have recently been revisited and reanalyzed in the context of three or more precisions. These new analyses show…

Numerical Analysis · Mathematics 2022-02-17 Eda Oktay , Erin Carson

In this paper we investigate the application of pseudo-transient-continuation (PTC) schemes for the numerical solution of semilinear elliptic partial differential equations, with possible singular perturbations. We will outline a residual…

Numerical Analysis · Mathematics 2016-07-07 Mario Amrein , Thomas P. Wihler

In this paper, we consider high-dimensional nonconvex square-root-loss regression problems and introduce a proximal majorization-minimization (PMM) algorithm for these problems. Our key idea for making the proposed PMM to be efficient is to…

Optimization and Control · Mathematics 2020-05-28 Peipei Tang , Chengjing Wang , Defeng Sun , Kim-Chuan Toh

A numerical study of an optimal control formulation for a shape optimization problem governed by an elliptic variational inequality is performed. The shape optimization problem is reformulated as a boundary control problem in a fixed…

Optimization and Control · Mathematics 2018-01-22 Raino A. E. Mäkinen

Low-rank tensor methods for the approximate solution of second-order elliptic partial differential equations in high dimensions have recently attracted significant attention. A critical issue is to rigorously bound the error of such…

Numerical Analysis · Mathematics 2014-12-15 Markus Bachmayr , Wolfgang Dahmen

The residual cutting (RC) method has been proposed for efficiently solving linear equations obtained from elliptic partial differential equations. Based on the RC, we have introduced the generalized residual cutting (GRC) method, which can…

Numerical Analysis · Computer Science 2018-02-02 Toshihiko Abe , Anthony Theodore Chronopoulos

This paper concerns the composite problem of minimizing the sum of a twice continuously differentiable function $f$ and a nonsmooth convex function. For this class of nonconvex and nonsmooth problems, by leveraging a practical inexactness…

Optimization and Control · Mathematics 2025-05-27 Ruyu Liu , Shaohua Pan , Yitian Qian

In this work we develop and analyze a semi-smooth Newton method for the general nonlinear conic programming problem. In particular, we study the problem with a generalized simplicial cone, i.e., the image of a symmetric cone under a linear…

Optimization and Control · Mathematics 2026-04-22 Nicolas F. Armijo , Yunier Bello Cruz , Gabriel Haeser

Policy iteration enjoys a local quadratic rate of contraction, but its iterations are computationally expensive for Markov decision processes (MDPs) with a large number of states. In light of the connection between policy iteration and the…

Optimization and Control · Mathematics 2022-11-09 Matilde Gargiani , Dominic Liao-McPherson , Andrea Zanelli , John Lygeros

In this paper, we consider a large class of nonlinear equations derived from first-order type methods for solving composite optimization problems. Traditional approaches to establishing superlinear convergence rates of semismooth…

Optimization and Control · Mathematics 2023-07-31 Jiang Hu , Tonghua Tian , Shaohua Pan , Zaiwen Wen

In this paper we present a nonmonotone line search subgradient algorithm tailored to upper-$\mathcal{C}^2$ functions. This is a family of nonsmooth and nonconvex functions that satisfies a nonsmooth and local version of the descent lemma,…

Optimization and Control · Mathematics 2026-04-22 Francisco J. Aragón-Artacho , Rubén Campoy , Pedro Pérez-Aros , David Torregrosa-Belén

Adaptive cubic regularization methods for solving nonconvex problems need the efficient computation of the trial step, involving the minimization of a cubic model. We propose a new approach in which this model is minimized in a low…

Optimization and Control · Mathematics 2024-12-02 Stefania Bellavia , Davide Palitta , Margherita Porcelli , Valeria Simoncini

This paper is concerned with $\ell_q\,(0<q<1)$-norm regularized minimization problems with a twice continuously differentiable loss function. For this class of nonconvex and nonsmooth composite problems, many algorithms have been proposed…

Optimization and Control · Mathematics 2023-06-27 Yuqia Wu , Shaohua Pan , Xiaoqi Yang

In this paper, we propose a scaled gradient modified non-monotone line search method for solving constrained minimization problems, and explore several specific properties of this method, namely, its convergence analysis. We discuss the…

Optimization and Control · Mathematics 2026-05-01 Qamrul Hasan Ansari , Feeroz Babu , D. R. Sahu , Jen Chih Yao

We study optimal control problems that are governed by semilinear elliptic partial differential equations that involve non-Lipschitzian nonlinearities. It is shown that, for a certain class of such PDEs, the solution map is Fr\'{e}chet…

Optimization and Control · Mathematics 2024-12-03 Constantin Christof

This paper is concerned with an optimal control problem governed by a non-smooth semilinear elliptic equation. We show that the control-to-state mapping is directionally differentiable and precisely characterize its Bouligand…

Optimization and Control · Mathematics 2018-01-29 Constantin Christof , Christian Clason , Christian Meyer , Stephan Walther

In many applications of practical interest, solutions of partial differential equation models arise as critical points of an underlying (energy) functional. If such solutions are saddle points, rather than being maxima or minima, then the…

Numerical Analysis · Mathematics 2020-09-07 Pascal Heid , Thomas P. Wihler

The Gauss-Seidel method has been used for more than 100 years as the standard method for the solution of linear systems of equations under certain restrictions. This method, as well as Cramer and Jacobi, is widely used in education and…

Numerical Analysis · Mathematics 2025-03-31 Luis Saucedo-Mora , Luis Irastorza-Valera