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Newton method is one of the most powerful methods for finding solutions of nonlinear equations and for proving their existence. In its "pure" form it has fast convergence near the solution, but small convergence domain. On the other hand…

Optimization and Control · Mathematics 2019-08-27 Boris Polyak , Andrey Tremba

This note considers the inexact cubic-regularized Newton's method (CR), which has been shown in \cite{Cartis2011a} to achieve the same order-level convergence rate to a secondary stationary point as the exact CR \citep{Nesterov2006}.…

Optimization and Control · Mathematics 2018-08-23 Zhe Wang , Yi Zhou , Yingbin Liang , Guanghui Lan

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…

This paper proposes and develops a new Newton-type algorithm to solve subdifferential inclusions defined by subgradients of extended-real-valued prox-regular functions. The proposed algorithm is formulated in terms of the second-order…

Optimization and Control · Mathematics 2022-09-16 Pham Duy Khanh , Boris Mordukhovich , Vo Thanh Phat

A new variant of Newton's method for empirical risk minimization is studied, where at each iteration of the optimization algorithm, the gradient and Hessian of the objective function are replaced by robust estimators taken from existing…

Machine Learning · Statistics 2023-07-18 Eirini Ioannou , Muni Sreenivas Pydi , Po-Ling Loh

We study the sparse phase retrieval problem, which seeks to recover a sparse signal from a limited set of magnitude-only measurements. In contrast to prevalent sparse phase retrieval algorithms that primarily use first-order methods, we…

Information Theory · Computer Science 2024-03-20 Jian-Feng Cai , Yu Long , Ruixue Wen , Jiaxi Ying

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

We show that the third order approximation function $M_f$, proposed by S. Amat, S. Busquier, S. Plaza, in \textit{J. Math. Anal. Appl.}, 366(2010), 24--32, for functions $f$ twice continuously differentiable and such that both $f$ and its…

Dynamical Systems · Mathematics 2025-11-04 Aurelian Gheondea , Mehmet Emre Şamcı

We present a practical implementation based on Newton's method to find all roots of several families of complex polynomials of degrees exceeding one billion ($10^9$) so that the observed complexity to find all roots is between $O(d\ln d)$…

Numerical Analysis · Mathematics 2023-08-09 Marvin Randig , Dierk Schleicher , Robin Stoll

We consider asynchronous versions of the first and second order Richardson methods for solving linear systems of equations. These methods depend on parameters whose values are chosen a priori. We explore the parameter values that can be…

Numerical Analysis · Mathematics 2020-09-07 Edmond Chow , Andreas Frommer , Daniel B. Szyld

We study the problem of minimizing a sum of convex objective functions where the components of the objective are available at different nodes of a network and nodes are allowed to only communicate with their neighbors. The use of…

Optimization and Control · Mathematics 2015-04-24 Aryan Mokhtari , Qing Ling , Alejandro Ribeiro

In this paper, we study Newton-conjugate gradient (Newton-CG) methods for minimizing a nonconvex function $f$ whose Hessian is $(H_f,\nu)$-H\"older continuous with modulus $H_f>0$ and exponent $\nu\in(0,1]$. Recently proposed Newton-CG…

Optimization and Control · Mathematics 2026-04-30 Ziyang Zeng , Junyu Zhang , Chuan He

We consider the inexact Newton methods $$ x_{n+1}^\d=x_n^\d-g_{\a_n}(F'(x_n^\d)^* F'(x_n^\d)) F'(x_n^\d)^* (F(x_n^\d)-y^\d) $$ for solving nonlinear ill-posed inverse problems $F(x)=y$ using the only available noise data $y^\d$ satisfying…

Numerical Analysis · Mathematics 2010-10-19 Qinian Jin

We present a Newton-type method that converges fast from any initialization and for arbitrary convex objectives with Lipschitz Hessians. We achieve this by merging the ideas of cubic regularization with a certain adaptive…

Optimization and Control · Mathematics 2023-03-02 Konstantin Mishchenko

We consider the problem of finding the minimizer of a convex function $F: \mathbb R^d \rightarrow \mathbb R$ of the form $F(w) := \sum_{i=1}^n f_i(w) + R(w)$ where a low-rank factorization of $\nabla^2 f_i(w)$ is readily available. We…

Optimization and Control · Mathematics 2016-07-07 Peng Xu , Jiyan Yang , Farbod Roosta-Khorasani , Christopher Ré , Michael W. Mahoney

This paper presents a modification of Secant method for finding roots of equations that uses three points for iteration instead of just two. The development of the mathematical formula to be used in the iteration process is provided…

Numerical Analysis · Mathematics 2019-02-26 Ababu Teklemariam Tiruneh

Newton's root finding method applied to a (transcendental) entire function f:C->C is the iteration of a meromorphic function N. It is well known that if for some starting value z, Newton's method converges to a point x in C, then f has a…

Dynamical Systems · Mathematics 2007-05-23 Xavier Buff , Johannes Rueckert

In this paper, we study iterative methods on the coefficients of the rational univariate representation (RUR) of a given algebraic set, called global Newton iteration. We compare two natural approaches to define locally quadratically…

Numerical Analysis · Computer Science 2014-04-23 Jonathan D. Hauenstein , Victor Pan , Agnes Szanto

We describe a method for calculating the roots of special functions satisfying second order linear ordinary differential equations. It exploits the recent observation that the solutions of a large class of such equations can be represented…

Numerical Analysis · Mathematics 2016-08-05 James Bremer

We investigate Newton's method for complex polynomials of arbitrary degree $d$, normalized so that all their roots are in the unit disk. For each degree $d$, we give an explicit set $\mathcal{S}_d$ of $3.33d\log^2 d(1 + o(1))$ points with…

Dynamical Systems · Mathematics 2016-03-18 Todor Bilarev , Magnus Aspenberg , Dierk Schleicher