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In this paper, we investigate global convergence properties of the inexact nonsmooth Newton method for solving the system of absolute value equations (AVE). Global $Q$-linear convergence is established under suitable assumptions. Moreover,…

Optimization and Control · Mathematics 2015-11-13 J. Y. Bello Cruz , O. P. Ferreira , L. F. Prudente

We propose a novel trust region method for solving a class of nonsmooth, nonconvex composite-type optimization problems. The approach embeds inexact semismooth Newton steps for finding zeros of a normal map-based stationarity measure for…

Optimization and Control · Mathematics 2023-10-04 Wenqing Ouyang , Andre Milzarek

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

An intriguing and unexpected result for students learning numerical analysis is that Newton's method, applied to the simple polynomial z^3 - 1 = 0 in the complex plane, leads to intricately interwoven basins of attraction of the roots. As…

chao-dyn · Physics 2008-02-03 Bogdan I. Epureanu , Henry S. Greenside

This is a research announcement on what is best termed `nonlocal' methods in mathematics. (This is not to be confused with global analysis.) The nonlocal formulation of physics in \cite{principia} points to a fresh viewpoint in mathematics:…

General Mathematics · Mathematics 2007-05-23 Mukul Patel

In design of optical systems based on LED (Light emitting diode) technology, a crucial task is to handle the unstructured data describing properties of optical elements in standard formats. This leads to the problem of data fitting within…

Other Computer Science · Computer Science 2016-04-27 David Kaljun , Joze Petrišič , Janez Žerovnik

Given only a collection of points sampled from a Riemannian manifold embedded in a Euclidean space, in this paper we propose a new method to solve elliptic partial differential equations (PDEs) supplemented with boundary conditions. Notice…

Numerical Analysis · Mathematics 2022-11-29 Ryan Vaughn , Tyrus Berry , Harbir Antil

The majority of model-based learned image reconstruction methods in medical imaging have been limited to uniform domains, such as pixelated images. If the underlying model is solved on nonuniform meshes, arising from a finite element method…

Image and Video Processing · Electrical Eng. & Systems 2021-07-12 William Herzberg , Daniel B. Rowe , Andreas Hauptmann , Sarah J. Hamilton

The problem of finding roots or solutions of a nonlinear partial differential equation may be formulated as the problem of minimizing a sum of squared residuals. One then defines an evolution equation so that in the asymptotic limit a…

Analysis of PDEs · Mathematics 2011-12-15 Parimah Kazemi , Robert Renka

In the graph node embedding problem, embedding spaces can vary significantly for different data types, leading to the need for different GNN model types. In this paper, we model the embedding update of a node feature as a Hamiltonian orbit…

Machine Learning · Computer Science 2023-05-31 Qiyu Kang , Kai Zhao , Yang Song , Sijie Wang , Wee Peng Tay

This study proposes a cubic regularization of the Newton method for generating weakly efficient points of unconstrained vector optimization problems under no convexity assumption on the objective function. It is observed that at a given…

Optimization and Control · Mathematics 2025-05-20 Debdas Ghosh

In this article, we consider a class of four-dimensional Einstein-Maxwell theory which is coupled non-minimally to a scalar field and the Gauss-Bonnet invariant. We mainly use the numerical methods to find the solutions to the theory, with…

General Relativity and Quantum Cosmology · Physics 2024-03-12 Michael Butler , Masoud Ghezelbash

We consider the proximal gradient method on Riemannian manifolds for functions that are possibly not geodesically convex. Starting from the forward-backward-splitting, we define an intrinsic variant of the proximal gradient method that uses…

Optimization and Control · Mathematics 2025-06-12 Ronny Bergmann , Hajg Jasa , Paula John , Max Pfeffer

This paper formulates an elementary algorithm for resolution of singularities in a neighborhood of a singular point over a field of characteristic zero. The algorithm is composed of finite sequences of Newton polyhedra and monomial…

Algebraic Geometry · Mathematics 2014-04-29 Sheng-Ming Ma

In this paper, we study a new iterative method for finding the fixed point of a weak Bregman relatively nonexpansive mapping and the set of solutions of generalized mixed equilibrium problems in Banach spaces.

Functional Analysis · Mathematics 2019-11-07 V. Darvish , K. Jantakarn , A. Kaewcharoen , N. Biranvand

We solve tensor balancing, rescaling an Nth order nonnegative tensor by multiplying N tensors of order N - 1 so that every fiber sums to one. This generalizes a fundamental process of matrix balancing used to compare matrices in a wide…

Methodology · Statistics 2018-10-30 Mahito Sugiyama , Hiroyuki Nakahara , Koji Tsuda

We propose a novel linesearch variant of the trust region normal map-based semismooth Newton method developed in [Ouyang and Milzarek, Math. Program. 212(1-2), 389--435 (2025)] for solving a class of nonsmooth, nonconvex composite-type…

Optimization and Control · Mathematics 2026-02-16 Hanfeng Zeng , Wenqing Ouyang , Andre Milzarek

This paper is dedicated to the problem of isolating and validating zeros of non-linear two point boundary value problems. We present a method for such purpose based on the Newton-Kantorovich Theorem to rigorously enclose isolated zeros of…

Analysis of PDEs · Mathematics 2022-05-24 Eduardo Ramos , Victor Nolasco , Marcio Gameiro

Newton's method is an ubiquitous tool to solve equations, both in the archimedean and non-archimedean settings -- for which it does not really differ. Broyden was the instigator of what is called "quasi-Newton methods". These methods use an…

Symbolic Computation · Computer Science 2020-09-04 Xavier Dahan , Tristan Vaccon

Recently, a Riemannian proximal Newton method has been developed for optimizing problems in the form of $\min_{x\in\mathcal{M}} f(x) + \mu \|x\|_1$, where $\mathcal{M}$ is a compact embedded submanifold and $f(x)$ is smooth. Although this…

Optimization and Control · Mathematics 2025-03-25 Wen Huang , Wutao Si