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We develop subgradient- and gradient-based methods for minimizing strongly convex functions under a notion which generalizes the standard Euclidean strong convexity. We propose a unifying framework for subgradient methods which yields two…

Optimization and Control · Mathematics 2016-08-19 Masaru Ito

This article develops a solution for an inverse problem through the generalized method of lines. We consider a Laplace equation on a domain with internal and external boundaries with standard Dirichlet boundary conditions. Also, we specify…

Optimization and Control · Mathematics 2019-07-05 Fabio Silva Botelho

We study an approximation method to solve nonlinear multi-term fractional differential equations with initial conditions or boundary conditions. First, we transform the nonlinear multi-term fractional differential equations with initial…

Mathematical Physics · Physics 2013-03-21 Hui-Chol Choe , Yong-Suk Kang

We consider spectral approximations to the conservative form of the two-sided Riemann-Liouville (R-L) and Caputo fractional differential equations (FDEs) with nonhomogeneous Dirichlet (fractional and classical, respectively) and Neumann…

Numerical Analysis · Mathematics 2018-07-13 Nan Wang , Zhiping Mao , Chengming Huang , George Em Karniadakis

A numerical scheme is presented for solving the Helmholtz equation with Dirichlet or Neumann boundary conditions on piecewise smooth open curves, where the curves may have corners and multiple junctions. Existing integral equation methods…

Numerical Analysis · Mathematics 2024-11-11 Johan Helsing , Shidong Jiang

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 Continuous p-Dispersion Problem (CpDP) with boundary constraints asks for the placement of a fixed number of points in a compact subset of Euclidean space such that the minimum distance between any two points, as well as the points and…

Optimization and Control · Mathematics 2026-03-02 Sanjay Manoj , Melkior Ornik

We analyze and test using Fourier extensions that minimize a Hilbert space norm for the purpose of solving partial differential equations (PDEs) on surfaces. In particular, we prove that the approach is arbitrarily high-order and also show…

Numerical Analysis · Mathematics 2025-12-30 Daniel R. Venn , Steven J. Ruuth

The authors propose a Nystrom method to approximate the solution of a boundary integral equation connected with the exterior Neumann problem for Laplace's equation on planar domains with corners. They prove the convergence and the stability…

Numerical Analysis · Mathematics 2015-04-15 Luisa Fermo , Concetta Laurita

In this paper, we study a generalized finite element method for solving second-order elliptic partial differential equations with rough coefficients. The method uses local approximation spaces computed by solving eigenvalue problems on…

Numerical Analysis · Mathematics 2025-07-17 Christian Alber , Peter Bastian , Moritz Hauck , Robert Scheichl

By employing the closest point method, we extend the applicability of minimizing movements to the surface PDE setting. The corresponding approximation methods are created, and their convergence is observed. The numerical methods are then…

Numerical Analysis · Mathematics 2024-09-06 Elliott Ginder , Karel Svadlenka , Takuma Muramatsu

In this paper, the generalized finite element method (GFEM) for solving second order elliptic equations with rough coefficients is studied. New optimal local approximation spaces for GFEMs based on local eigenvalue problems involving a…

Numerical Analysis · Mathematics 2021-12-22 Chupeng Ma , Robert Scheichl , Tim Dodwell

We propose a globally convergent numerical method to compute solutions to a general class of quasi-linear PDEs with both Neumann and Dirichlet boundary conditions. Combining the quasi-reversibility method and a suitable Carleman weight…

Numerical Analysis · Mathematics 2022-10-10 Loc Hoang Nguyen

Diffuse domain methods (DDMs) have garnered significant attention for approximating solutions to partial differential equations on complex geometries. These methods implicitly represent the geometry by replacing the sharp boundary interface…

Analysis of PDEs · Mathematics 2025-04-25 Toai Luong , Tadele Mengesha , Steven M. Wise , Ming Hei Wong

Completely positive factorization (CPF) is a critical task with applications in many fields. This paper proposes a novel method for the CPF. Based on the idea of exterior point iteration, an optimization model is given, which aims to…

Optimization and Control · Mathematics 2021-02-17 Zhenyue Zhang , Bingjie Li

In this article we develop the Constraint Energy Minimizing Generalized Multiscale Finite Element Method (CEM-GMsFEM) for elliptic partial differential equations with inhomogeneous Dirichlet, Neumann, and Robin boundary conditions, and the…

Numerical Analysis · Mathematics 2022-01-14 Changqing Ye , Eric T. Chung

We present a unified hard-constraint framework for solving geometrically complex PDEs with neural networks, where the most commonly used Dirichlet, Neumann, and Robin boundary conditions (BCs) are considered. Specifically, we first…

Machine Learning · Computer Science 2023-06-06 Songming Liu , Zhongkai Hao , Chengyang Ying , Hang Su , Jun Zhu , Ze Cheng

In this study, we presented the high-order fundamental solutions and general solutions of convection-diffusion equation. To demonstrate their efficacy, we applied the high-order general solutions to the boundary particle method (BPM) for…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 W. Chen

Defined mathematically as critical points of surface area subject to a volume constraint, constant mean curvatures (CMC) surfaces are idealizations of interfaces occurring between two immiscible fluids. Their behavior elucidates phenomena…

Numerical Analysis · Mathematics 2018-08-07 Nicholas D. Brubaker

The proximal gradient method is a generic technique introduced to tackle the non-smoothness in optimization problems, wherein the objective function is expressed as the sum of a differentiable convex part and a non-differentiable…

Numerical Analysis · Mathematics 2024-01-19 Abdeslem Hafid Bentbib , Khalide Jbilou , Ridwane Tahiri