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We investigate quasi-Newton methods for minimizing a strictly convex quadratic function which is subject to errors in the evaluation of the gradients. The methods all give identical behavior in exact arithmetic, generating minimizers of…

Optimization and Control · Mathematics 2025-02-26 Shen Peng , Gianpiero Canessa , David Ek , Anders Forsgren

The random feature method (RFM), a mesh-free machine learning-based framework, has emerged as a promising alternative for solving PDEs on complex domains. However, for large three-dimensional nonlinear problems, attaining high accuracy…

Numerical Analysis · Mathematics 2025-10-07 Longze Tan

Augmented Krylov subspace methods aid in accelerating the convergence of a standard Krylov subspace method by including additional vectors in the search space. A residual projection framework based on residual (Petrov-) Galerkin constraints…

Numerical Analysis · Mathematics 2023-05-19 Liam Burke , Kirk M. Soodhalter

This work proposes novel techniques for the efficient numerical simulation of parameterized, unsteady partial differential equations. Projection-based reduced order models (ROMs) such as the reduced basis method employ a (Petrov-)Galerkin…

Numerical Analysis · Mathematics 2023-12-05 Nicholas Mueller , Santiago Badia

The linear conjugate gradient method is widely used in physical simulation, particularly for solving large-scale linear systems derived from Newton's method. The nonlinear conjugate gradient method generalizes the conjugate gradient method…

Optimization and Control · Mathematics 2024-05-15 Xing Shen , Runyuan Cai , Mengxiao Bi , Tangjie Lv

In this paper, we combine discrete empirical interpolation techniques, global mode decomposition methods, and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM), to reduce the computational…

Numerical Analysis · Mathematics 2023-07-19 Manal Alotaibi , Victor M. Calo , Yalchin Efendiev , Juan Galvis , Mehdi Ghommem

This paper presents a novel and straightforward compact reconstruction procedure for the high-order finite volume method on unstructured grids. In this procedure, we constructed a linear approximation relationship between the mean values…

Fluid Dynamics · Physics 2026-03-27 Ling Wen , Yan-Tao Yang , Qing-Dong Cai

We propose an acceleration scheme for first-order methods (FOMs) for convex quadratic programs (QPs) that is analogous to Anderson acceleration and the Generalized Minimal Residual algorithm for linear systems. We motivate our proposed…

Optimization and Control · Mathematics 2026-04-09 Gabriel Berk Pereira , Paul J. Goulart

The image-based visual servoing without models of system is challenging since it is hard to fetch an accurate estimation of hand-eye relationship via merely visual measurement. Whereas, the accuracy of estimated hand-eye relationship…

Robotics · Computer Science 2022-11-22 Haibin Zeng , Yueyong Lyu , Jiaming Qi , Shuangquan Zou , Tanghao Qin , Wenyu Qin

We consider here a cell-centered finite difference approximation of the Richards equation in three dimensions, averaging for interface values the hydraulic conductivity $K=K(p)$, a highly nonlinear function, by arithmetic, upstream, and…

Numerical Analysis · Mathematics 2022-07-18 Daniele Bertaccini , Pasqua D'Ambra , Fabio Durastante , Salvatore Filippone

Finding the optimal hyperparameters of a model can be cast as a bilevel optimization problem, typically solved using zero-order techniques. In this work we study first-order methods when the inner optimization problem is convex but…

This paper presents a general and robust method for the fluid-structure interaction of membranes and shells undergoing large displacement and large added-mass effects by coupling an immersed-boundary method with a shell finite-element…

Fluid Dynamics · Physics 2023-08-15 Marin Lauber , Gabriel D. Weymouth , Georges Limbert

This paper proposes and justifies two globally convergent Newton-type methods to solve unconstrained and constrained problems of nonsmooth optimization by using tools of variational analysis and generalized differentiation. Both methods are…

Optimization and Control · Mathematics 2023-04-27 Pham Duy Khanh , Boris Mordukhovich , Vo Thanh Phat , Dat Ba Tran

This work presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation…

Numerical Analysis · Mathematics 2016-01-22 Kevin Carlberg , Virginia Forstall , Ray Tuminaro

The discretization of the double-layer potential integral equation for the interior Dirichlet Laplace problem in a domain with smooth boundary results in a linear system that has a bounded condition number. Thus, the number of iterations…

Numerical Analysis · Mathematics 2014-02-27 Bryan Quaife , George Biros

We consider minimization of indefinite quadratics with either trust-region (norm) constraints or cubic regularization. Despite the nonconvexity of these problems we prove that, under mild assumptions, gradient descent converges to their…

Optimization and Control · Mathematics 2020-08-17 Yair Carmon , John C. Duchi

The classic method for computing the spectral decomposition of a real symmetric matrix, the Jacobi algorithm, can be accelerated by using mixed precision arithmetic. The Jacobi algorithm is aiming to reduce the off-diagonal entries…

Numerical Analysis · Mathematics 2025-09-03 Zhengbo Zhou

We develop a rigid multiblob method for numerically solving the mobility problem for suspensions of passive and active rigid particles of complex shape in Stokes flow in unconfined, partially confined, and fully confined geometries. As in a…

Soft Condensed Matter · Physics 2017-02-08 F. Balboa Usabiaga , B. Kallemov , B. Delmotte , A. Pal Singh Bhalla , B. E. Griffith , A. Donev

Krylov methods provide a fast and highly parallel numerical tool for the iterative solution of many large-scale sparse linear systems. To a large extent, the performance of practical realizations of these methods is constrained by the…

Mathematical Software · Computer Science 2020-09-28 José I. Aliaga , Hartwig Anzt , Thomas Grützmacher , Enrique S. Quintana-Ortí , Andrés E. Tomás

This paper presents two new augmented flexible (AF)-Krylov subspace methods, AF-GMRES and AF-LSQR, to compute solutions of large-scale linear discrete ill-posed problems that can be modeled as the sum of two independent random variables,…

Numerical Analysis · Mathematics 2023-10-10 Malena Sabate Landman , Jiahua Jiang , Jianru Zhang , Wuwei Ren
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