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The $p$-adic Newton polygon is a visual tool that encodes information about the roots and factorization of a polynomial relative to a prime $p$. In this article, we investigate how the Newton polygon changes under polynomial composition. If…

Number Theory · Mathematics 2025-01-29 Rylan Gajek-Leonard , Uri Tomer

In this paper, we propose a new method that combines the inexact Newton method with a procedure to obtain a feasible inexact projection for solving constrained smooth and nonsmooth equations. The local convergence theorems are established…

Optimization and Control · Mathematics 2019-03-19 Fabiana R. de Oliveira , Orizon P. Ferreira

In this paper we study the Newton's method for finding a singularity of a differentiable vector field defined on a Riemannian manifold. Under the assumption of invertibility of covariant derivative of the vector field at its singularity, we…

Optimization and Control · Mathematics 2016-11-15 Teles A. Fernandes , Orizon P. Ferreira , Yuan J. Yun

When studying the multilinear PageRank problem, a system of polynomial equations needs to be solved. In this paper, we develop convergence theory for a modified Newton method in a particular parameter regime. The sequence of vectors…

Numerical Analysis · Mathematics 2017-01-23 Pei-Chang Guo

We study a Newton-like method for the minimization of an objective function that is the sum of a smooth convex function and an l-1 regularization term. This method, which is sometimes referred to in the literature as a proximal Newton…

Optimization and Control · Mathematics 2013-09-16 Richard H. Byrd , Jorge Nocedal , Figen Oztoprak

We study a variant of Newton's algorithm applied to under-determined systems of non-smooth equations. The notion of regularity employed in our work is based on Newton differentiability, which generalizes semi-smoothness. The classic notion…

Optimization and Control · Mathematics 2025-04-28 Titus Pinta

In this paper we study Newton's method for solving the generalized equation $F(x)+T(x)\ni 0$ in Hilbert spaces, where $F$ is a Fr\'echet differentiable function and $T$ is set-valued and maximal monotone. We show that this method is local…

Numerical Analysis · Mathematics 2016-08-02 Gilson N. Silva

This paper proposes new proximal Newton-type methods with a diagonal metric for solving composite optimization problems whose objective function is the sum of a twice continuously differentiable function and a proper closed directionally…

Optimization and Control · Mathematics 2023-10-11 Shotaro Yagishita , Shummin Nakayama

The Newton-Raphson method is a fundamental root-finding technique with numerous applications in physics. In this study, we propose a parameterized variant of the Newton-Raphson method, inspired by principles from physics. Through analytical…

Numerical Analysis · Mathematics 2024-08-02 Junghyo Jo , Alexandre Wagemakers , Vipul Periwal

Quasi-Newton methods form an important class of methods for solving nonlinear optimization problems. In such methods, first order information is used to approximate the second derivative. The aim is to mimic the fast convergence that can be…

Optimization and Control · Mathematics 2025-02-20 Aban Ansari-Önnestam , Anders Forsgren

We analyze the performance of a variant of Newton method with quadratic regularization for solving composite convex minimization problems. At each step of our method, we choose regularization parameter proportional to a certain power of the…

Optimization and Control · Mathematics 2022-08-12 Nikita Doikov , Konstantin Mishchenko , Yurii Nesterov

Using the interplay between topological, combinatorial, and geometric properties of polynomials and analytic results (primarily the covering structure and distortion estimates), we analyze a path-lifting method for finding approximate…

Numerical Analysis · Mathematics 2018-01-08 Myong-Hi Kim , Marco Martens , Scott Sutherland

We specify a small set, consisting of $O(d(\log\log d)^2)$ points, that intersects the basins under Newton's method of \emph{all} roots of \emph{all} (suitably normalized) complex polynomials of fixed degrees $d$, with arbitrarily high…

Dynamical Systems · Mathematics 2011-08-31 Béla Bollobás , Malte Lackmann , Dierk Schleicher

In recent years, the proximal gradient method and its variants have been generalized to Riemannian manifolds for solving optimization problems with an additively separable structure, i.e., $f + h$, where $f$ is continuously differentiable,…

Optimization and Control · Mathematics 2024-04-04 Wutao Si , P. -A. Absil , Wen Huang , Rujun Jiang , Simon Vary

In this paper, we study the Newton polygons for the $L$-functions of $n$-variable generalized Kloosterman sums. Generally, the Newton polygon has a topological lower bound, called the Hodge polygon. In order to determine the Hodge polygon,…

Number Theory · Mathematics 2021-08-03 Chunlin Wang , Liping Yang

We analyze the convergence of quasi-Newton methods in exact and finite precision arithmetic. In particular, we derive an upper bound for the stagnation level and we show that any sufficiently exact quasi-Newton method will converge…

We present generalizations of Newton's method that incorporate derivatives of an arbitrary order $d$ but maintain a polynomial dependence on dimension in their cost per iteration. At each step, our $d^{\text{th}}$-order method uses…

Optimization and Control · Mathematics 2024-06-13 Amir Ali Ahmadi , Abraar Chaudhry , Jeffrey Zhang

This work investigates the application of the Newton's method for the numerical solution of a nonlinear boundary value problem formulated through an ordinary differential equation (ODE). Nonlinear ODEs arise in various mathematical modeling…

In the paper, a Newton-type method for the solution of generalized equations (GEs) is derived, where the linearization concerns both the single-valued and the multi-valued part of the considered GE. The method is based on the new notion of…

Optimization and Control · Mathematics 2019-04-22 H. Gfrerer , J. V. Outrata

In this paper, we modify and apply the recently introduced Mixed Newton Method, which is originally designed for minimizing real-valued functions of complex variables, to the minimization of real-valued functions of real variables by…