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In this paper, we investigate inexact variants of dual-primal isogeometric tearing and interconnecting methods for solving large-scale systems of linear equations arising from Galerkin isogeometric discretizations of elliptic boundary value…

Numerical Analysis · Mathematics 2021-12-30 Christoph Hofer , Ulrich Langer , Stefan Takacs

Solving different types of optimization models (including parameters fitting) for support vector machines on large-scale training data is often an expensive computational task. This paper proposes a multilevel algorithmic framework that…

Machine Learning · Statistics 2014-10-14 Talayeh Razzaghi , Ilya Safro

Inspired by multigrid methods for linear systems of equations, multilevel optimization methods have been proposed to solve structured optimization problems. Multilevel methods make more assumptions regarding the structure of the…

Optimization and Control · Mathematics 2019-11-27 Chin Pang Ho , Michal Kocvara , Panos Parpas

We introduce new multilevel methods for solving large-scale unconstrained optimization problems. Specifically, the philosophy of multilevel methods is applied to Newton-type methods that regularize the Newton sub-problem using second order…

Optimization and Control · Mathematics 2024-07-16 Nick Tsipinakis , Panos Parpas

This work develops a nonlinear multigrid method for diffusion problems discretized by cell-centered finite volume methods on general unstructured grids. The multigrid hierarchy is constructed algebraically using aggregation of degrees of…

Numerical Analysis · Mathematics 2020-10-29 Chak Shing Lee , François Hamon , Nicola Castelletto , Panayot S. Vassilevski , Joshua White

Two-level domain decomposition (DD) methods are very powerful techniques for the efficient numerical solution of partial differential equations (PDEs). A two-level domain decomposition method requires two main components: a one-level…

Numerical Analysis · Mathematics 2021-04-22 Gabriele Ciaramella , Tommaso Vanzan

Many problems in modern robotics can be addressed by modeling them as bilevel optimization problems. In this work, we leverage augmented Lagrangian methods and recent advances in automatic differentiation to develop a general-purpose…

Robotics · Computer Science 2019-07-03 Benoit Landry , Zachary Manchester , Marco Pavone

Collocation boundary element methods for integral equations are easier to implement than Galerkin methods because the elements of the discretization matrix are given by lower-dimensional integrals. For that same reason, the matrix assembly…

Numerical Analysis · Mathematics 2021-04-01 Georg Maierhofer , Daan Huybrechs

The solution to partial differential equations using deep learning approaches has shown promising results for several classes of initial and boundary-value problems. However, their ability to surpass, particularly in terms of accuracy,…

Numerical Analysis · Mathematics 2023-08-23 Ziad Aldirany , Régis Cottereau , Marc Laforest , Serge Prudhomme

We propose a multilevel approach for trace systems resulting from hybridized discontinuous Galerkin (HDG) methods. The key is to blend ideas from nested dissection, domain decomposition, and high-order characteristic of HDG discretizations.…

Numerical Analysis · Mathematics 2020-02-19 Sriramkrishnan Muralikrishnan , Tan Bui-Thanh , John N. Shadid

A wide variety of (fixed-point) iterative methods for the solution of nonlinear equations (in Hilbert spaces) exists. In many cases, such schemes can be interpreted as iterative local linearization methods, which, as will be shown, can be…

Numerical Analysis · Mathematics 2019-10-16 Pascal Heid , Thomas P. Wihler

This paper deals with speeding up the convergence of a class of two-step iterative methods for solving linear systems of equations. To implement the acceleration technique, the residual norm associated with computed approximations for each…

Numerical Analysis · Mathematics 2024-04-24 Fatemeh P. A. Beik , Michele Benzi , Mehdi Najafi-Kalyani

This paper studies the Craig variant of the Golub-Kahan bidiagonalization algorithm as an iterative solver for linear systems with saddle point structure. Such symmetric indefinite systems in 2x2 block form arise in many applications, but…

Computational Engineering, Finance, and Science · Computer Science 2018-08-24 Mario Arioli , Carola Kruse , Ulrich Ruede , Nicolas Tardieu

This paper is devoted to the multigrid convergence analysis for the linear systems arising from the conforming linear finite element discretization of the second order elliptic equations with anisotropic diffusion. The multigrid convergence…

Numerical Analysis · Mathematics 2011-05-09 Guozhu Yu , Jinchao Xu , Ludmil Zikatanov

Solving linear systems is often the computational bottleneck in real-life problems. Iterative solvers are the only option due to the complexity of direct algorithms or because the system matrix is not explicitly known. Here, we develop a…

Numerical Analysis · Computer Science 2020-10-08 Joris Tavernier , Jaak Simm , Karl Meerbergen , Yves Moreau

A multilevel correction scheme is proposed to solve defective and nodefective of nonsymmetric partial differential operators by the finite element method. The method includes multi correction steps in a sequence of finite element spaces. In…

Numerical Analysis · Mathematics 2016-09-27 Hehu Xie , Zhimin Zhang

In this paper, a second-order linearized discontinuous Galerkin method on general meshes, which treats the backward differentiation formula of order two (BDF2) and Crank-Nicolson schemes as special cases, is proposed for solving the…

Numerical Analysis · Mathematics 2025-12-16 Zhen Guan , Xianxian Cao

A parallelizable iterative procedure based on domain decomposition is presented and analyzed for weak Galerkin finite element methods for second order elliptic equations. The convergence analysis is established for the decomposition of the…

Numerical Analysis · Mathematics 2022-04-12 Chunmei Wang , Junping Wang , Shangyou Zhang

We propose a new approach to solving bilevel optimization problems, intermediate between solving full-system optimality conditions with a Newton-type approach, and treating the inner problem as an implicit function. The overall idea is to…

Optimization and Control · Mathematics 2024-05-08 Ensio Suonperä , Tuomo Valkonen

We develop a convergence theory for non-monotone approximation schemes for fully nonlinear parabolic partial differential equations. Modern computational methods such as kernel-based collocation, spectral methods, physics-informed neural…

Numerical Analysis · Mathematics 2026-05-08 Yumiharu Nakano