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In this paper, we study the Gauss-Newton method for a special class of systems of nonlinear equation. Under the hypothesis that the derivative of the function under consideration satisfies a majorant condition, semi-local convergence…

Optimization and Control · Mathematics 2012-06-21 Max L. N. Gonçalves , Paulo R. Oliveira

This paper deals with the Darcy-Forchheimer problem with two kinds of boundary conditions. We discretize the system by using the finite element methods and we propose two iterative schemes to solve the discrete problems. The well-posedness…

Numerical Analysis · Mathematics 2021-11-23 Toni Sayah

We consider a system of Fokker-Planck-Kolmogorov (FPK) equations, where the dependence of the coefficients is nonlinear and nonlocal in time with respect to the unknowns. We extend the numerical scheme proposed and studied recently by the…

Numerical Analysis · Mathematics 2018-05-03 Elisabetta Carlini , Francisco J. Silva

In this paper, we propose new proximal Newton-type methods for convex optimization problems in composite form. The applications include model predictive control (MPC) and embedded MPC. Our new methods are computationally attractive since…

Optimization and Control · Mathematics 2020-07-21 Ilan Adler , Zhiyue Tom Hu , Tianyi Lin

In a recent joint work, the author has developed a modification of Newton's method, named New Q-Newton's method, which can avoid saddle points and has quadratic rate of convergence. While good theoretical convergence guarantee has not been…

Optimization and Control · Mathematics 2021-09-10 Tuyen Trung Truong

Flexible sparsity regularization means stably approximating sparse solutions of operator equations by using coefficient-dependent penalizations. We propose and analyse a general nonconvex approach in this respect, from both theoretical and…

Optimization and Control · Mathematics 2021-11-12 Daria Ghilli , Dirk A. Lorenz , Elena Resmerita

In this paper, a class of optimization problems with nonlinear inequality constraints is discussed. Based on the ideas of sequential quadratic programming algorithm and the method of strongly sub-feasible directions, a new superlinearly…

Optimization and Control · Mathematics 2012-06-28 Jin-Bao Jian , Chuan-Hao Guo , Chun-Ming Tang , Yan-Qin Bai

This paper considers the generalized continuation Newton method and thetrust-region updating strategy for the underdetermined system of nonlinear equations. Moreover, in order to improve its computational efficiency, the new method will not…

Numerical Analysis · Mathematics 2021-05-26 Xin-long Luo , Hang Xiao

It is well known that the Newton method may not converge when the initial guess does not belong to a specific quadratic convergence region. We propose a family of new variants of the Newton method with the potential advantage of having a…

Numerical Analysis · Mathematics 2021-03-30 Regina S. Burachik , Bethany I. Caldwell , C. Yalçın Kaya

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 investigate the convergence of McKean-Vlasov diffusions in a nonconvex landscape. These processes are linked to nonlinear partial differential equations. According to our previous results, there are at least three stationary measures…

Probability · Mathematics 2013-05-27 Julian Tugaut

In distributed optimization and distributed numerical linear algebra, we often encounter an inversion bias: if we want to compute a quantity that depends on the inverse of a sum of distributed matrices, then the sum of the inverses does not…

Machine Learning · Computer Science 2019-05-29 Michał Dereziński , Michael W. Mahoney

We show, in general, how to transform the nonautonomous nonlinear Schroedinger equation with quadratic Hamiltonians into the standard autonomous form that is completely integrable by the familiar inverse scattering method in nonlinear…

Mathematical Physics · Physics 2011-04-19 Sergei K. Suslov

This paper proposes several novel optimization algorithms for minimizing a nonlinear objective function. The algorithms are enlightened by the optimal state trajectory of an optimal control problem closely related to the minimized objective…

Optimization and Control · Mathematics 2025-04-01 Hongxia Wang , Yeming Xu , Ziyuan Guo , Huanshui Zhang

This article deals with the numerical integration in time of nonlinear Schr\"odinger equations. The main application is the numerical simulation of rotating Bose-Einstein condensates. The authors perform a change of unknown so that the…

Analysis of PDEs · Mathematics 2017-01-31 Christophe Besse , Guillaume Dujardin , Ingrid Lacroix-Violet

This paper extends the SQP-approach of the well-known bundle-Newton method for nonsmooth unconstrained minimization to the nonlinearly constrained case. Instead of using a penalty function or a filter or an improvement function to deal with…

Optimization and Control · Mathematics 2015-06-29 Hannes Fendl , Hermann Schichl

We consider a higher-order Milstein scheme for stochastic partial differential equations with trace class noise which fulfill a certain commutativity condition. A novel technique to generally improve the order of convergence of Taylor…

Numerical Analysis · Mathematics 2018-08-15 Claudine Leonhard , Andreas Rößler

The following document presents a possible solution and a brief stability analysis for a nonlinear system, which is obtained by studying the possibility of building a hybrid solar receiver; It is necessary to mention that the solution of…

Numerical Analysis · Mathematics 2024-04-25 A. Torres-Hernandez , F. Brambila-Paz , P. M. Rodrigo , E. De-la-Vega , C. C. Calabrese

This paper proposes and justifies two globally convergent Newton-type methods to solve unconstrained and constrained problems of nonsmooth optimization by using tools of variational analysis and generalized differentiation. Both methods are…

Optimization and Control · Mathematics 2023-04-27 Pham Duy Khanh , Boris Mordukhovich , Vo Thanh Phat , Dat Ba Tran

This paper presents an iterative method suitable for inverting semilinear problems which are important kernels in many numerical applications. The primary idea is to employ a parametrization that is able to reduce semilinear problems into…

Numerical Analysis · Mathematics 2019-08-02 Prosper Torsu