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Globalization concepts for Newton-type iteration schemes are widely used when solving nonlinear problems numerically. Most of these schemes are based on a predictor/corrector step size methodology with the aim of steering an initial guess…

Numerical Analysis · Mathematics 2019-10-09 Mario Amrein

In this work, we propose a nonlinear stabilization technique for scalar conservation laws with implicit time stepping. The method relies on an artificial diffusion method, based on a graph-Laplacian operator. It is nonlinear, since it…

Numerical Analysis · Computer Science 2016-12-23 Santiago Badia , Jesús Bonilla

In finance, implied volatility is an important indicator that reflects the market situation immediately. Many practitioners estimate volatility using iteration methods, such as the Newton--Raphson (NR) method. However, if numerous implied…

Computational Finance · Quantitative Finance 2022-10-31 Geon Lee , Tae-Kyoung Kim , Hyun-Gyoon Kim , Jeonggyu Huh

We consider empirical risk minimization for large-scale datasets. We introduce Ada Newton as an adaptive algorithm that uses Newton's method with adaptive sample sizes. The main idea of Ada Newton is to increase the size of the training set…

Machine Learning · Computer Science 2016-05-26 Aryan Mokhtari , Alejandro Ribeiro

We focus here on a class of fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. We design a novel second-order fully discrete mixed finite element method to…

Numerical Analysis · Mathematics 2020-08-28 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

Proximal methods are known to identify the underlying substructure of nonsmooth optimization problems. Even more, in many interesting situations, the output of a proximity operator comes with its structure at no additional cost, and…

Optimization and Control · Mathematics 2023-02-10 Gilles Bareilles , Franck Iutzeler , Jérôme Malick

This paper concerns developing a numerical method of the Newton type to solve systems of nonlinear equations described by nonsmooth continuous functions. We propose and justify a new generalized Newton algorithm based on graphical…

Optimization and Control · Mathematics 2010-09-03 T. Hoheisel , C. Kanzow , B. S. Mordukhovich , H. Phan

Numerical simulation of ordinary differential equations (ODEs) can be challenging when the system exhibits high accelerations and rapidly changing dynamics. Under these conditions the ODE solver often needs to take very small time steps in…

Numerical Analysis · Mathematics 2026-05-11 Andrew Tagg , Andrew Frandsen , Andrew Ning

We investigate the use of piecewise linear systems, whose coefficient matrix is a piecewise constant function of the solution itself. Such systems arise, for example, from the numerical solution of linear complementarity problems and in the…

Numerical Analysis · Mathematics 2012-06-21 Luigi Brugnano , Alessandra Sestini

Newton's Method is widely used to find the solution of complex non-linear simulation problems in Computer Graphics. To guarantee a descent direction, it is common practice to clamp the negative eigenvalues of each element Hessian prior to…

Graphics · Computer Science 2026-05-26 José Antonio Fernández-Fernández , Fabian Löschner , Jan Bender

Newton's method is used to approximate roots of complex valued functions f by creating a sequence of points that converges to a root of f in the usual topology. For any field K equipped with a set of pairwise inequivalent absolute values…

Number Theory · Mathematics 2013-02-15 Xander Faber , Adam Towsley

Fluid-structure interaction models are used to study how a material interacts with different fluids at different Reynolds numbers. Examining the same model not only for different fluids but also for different solids allows to optimize the…

Numerical Analysis · Mathematics 2023-07-28 Peter Benner , Thomas Richter , Roman Weinhandl

In this paper, we propose an inexact proximal Newton-type method for nonconvex composite problems. We establish the global convergence rate of the order $\mathcal{O}(k^{-1/2})$ in terms of the minimal norm of the KKT residual mapping and…

Optimization and Control · Mathematics 2024-12-26 Hong Zhu

We propose a novel neural preconditioned Newton (NP-Newton) method for solving parametric nonlinear systems of equations. To overcome the stagnation or instability of Newton iterations caused by unbalanced nonlinearities, we introduce a…

Numerical Analysis · Mathematics 2025-11-13 Youngkyu Lee , Shanqing Liu , Jerome Darbon , George Em Karniadakis

We are interested in a reduced order method for the efficient simulation of blood flow in arteries. The blood dynamics is modeled by means of the incompressible Navier-Stokes equations. Our algorithm is based on an approximated…

Numerical Analysis · Mathematics 2021-04-07 Luca Pegolotti , Martin Pfaller , Alison Marsden , Simone Deparis

Model reduction methods are relevant when the computation time of a full convection-diffusion-reaction simulation based on detailed chemical reaction mechanisms is too large. In this article, we review a model reduction approach based on…

Computational Physics · Physics 2014-05-20 Dirk Lebiedz , Jochen Siehr

This paper presents a novel implicit scheme for the constraint resolution in real-time finite element simulations in the presence of contact and friction. Instead of using the standard motion correction scheme, we propose an iterative…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-06-13 Ziqiu Zeng , Hadrien Courtecuisse

Nonlinear systems arising from time integrators like Backward Euler can sometimes be reformulated as optimization problems, known as incremental potentials. We show through a comprehensive experimental analysis that the widely used…

In [1], the non-linear space-time Hasegawa-Mima plasma equation is formulated as a coupled system of two linear PDE's, a solution of which is a pair (u, w). The first equation is of hyperbolic type and the second of elliptic type.…

Numerical Analysis · Mathematics 2022-02-04 Sophie M. Moufawad , Nabil R. Nassif

The study of Newton's method in complex-valued neural networks faces many difficulties. In this paper, we derive Newton's method backpropagation algorithms for complex-valued holomorphic multilayer perceptrons, and investigate the…

Complex Variables · Mathematics 2014-06-23 Diana Thomson La Corte , Yi Ming Zou