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This paper is concerned with global-in-time, nonoverlapping domain decomposition methods for the mixed formulation of the diffusion problem. Two approaches are considered: one uses the time-dependent Steklov-Poincar\'e operator and the…

Numerical Analysis · Mathematics 2013-12-30 Thi Thao Phuong Hoang , Jérôme Jaffré , Caroline Japhet , Michel Kern , Jean Roberts

Optimal power flow (OPF) is an important problem for power generation and it is in general non-convex. With the employment of renewable energy, it will be desirable if OPF can be solved very efficiently so its solution can be used in real…

Optimization and Control · Mathematics 2011-09-27 Albert Y. S. Lam , Baosen Zhang , David Tse

This paper presents a novel hybrid approach for coupling subdomain-local non-intrusive Operator Inference (OpInf) reduced order models (ROMs) with each other and with subdomain-local high-fidelity full order models (FOMs) with using the…

Numerical Analysis · Mathematics 2026-01-06 Irina Tezaur , Eric Parish , Anthony Gruber , Ian Moore , Christopher Wentland , Alejandro Mota

This paper proposes a component-based dual decomposition of the nonconvex AC optimal power flow (OPF) problem, where the modified dual function is solved in a distributed fashion. The main contribution of this work is that is demonstrates…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-08-23 Sleiman Mhanna , Gregor Verbic , Archie Chapman

We prove linear convergence for a new family of modified Dirichlet--Neumann methods applied to quasilinear parabolic equations, as well as the convergence of the Robin--Robin method. Such nonoverlapping domain decomposition methods are…

Numerical Analysis · Mathematics 2023-08-30 Emil Engström , Eskil Hansen

We shall derive and propose several efficient overlapping domain decomposition methods for solving some typical linear inverse problems, including the identiffication of the flux, the source strength and the initial temperature in second…

Numerical Analysis · Mathematics 2013-09-10 Jiang Daijun , Feng Hui , Zou Jun

In this paper, we propose a novel overlapping domain decomposition method that can be applied to various problems in variational imaging such as total variation minimization. Most of recent domain decomposition methods for total variation…

Numerical Analysis · Mathematics 2020-06-23 Jongho Park

A fast algorithm (linear in the degrees of freedom) for the solution of linear variable-coefficient rational-order fractional integral and differential equations is described. The approach is related to the ultraspherical method for…

Numerical Analysis · Mathematics 2017-12-04 Nicholas Hale , Sheehan Olver

The piecewise constant Mumford-Shah (PCMS) model and the Rudin-Osher-Fatemi (ROF) model are two important variational models in image segmentation and image restoration, respectively. In this paper, we explore a linkage between these…

Numerical Analysis · Mathematics 2020-05-14 Xiaohao Cai , Raymond Chan , Carola-Bibiane Schonlieb , Gabriele Steidl , Tieyong Zeng

The massive integration of distributed energy resources changes the operational demands of the electric power distribution system, motivating optimization-based approaches. The added computational complexities of the resulting optimal power…

Optimization and Control · Mathematics 2023-07-04 Yunqi Luo , Rabayet Sadnan , Bala Krishnamoorthy , Anamika Dubey

Constructing effective image priors is critical to solving ill-posed inverse problems in image processing and imaging. Recent works proposed to exploit image non-local similarity for inverse problems by grouping similar patches and…

Computer Vision and Pattern Recognition · Computer Science 2021-05-25 Lanqing Guo , Zhiyuan Zha , Saiprasad Ravishankar , Bihan Wen

The optimal power flow (OPF) problem, which plays a central role in operating electrical networks is considered. The problem is nonconvex and is in fact NP hard. Therefore, designing efficient algorithms of practical relevance is crucial,…

Optimization and Control · Mathematics 2014-08-20 S. Magnússon , P. C. Weeraddana , C. Fischione

In this work, we consider compressible single-phase flow problems in a porous media containing a fracture. In the latter, a non-linear pressure-velocity relation is prescribed. Using a non-overlapping domain decomposition procedure, we…

In this paper we are interested in the "fast path" fracture and we aim to use global-in-time, nonoverlapping domain decomposition methods to model flow and transport problems in a porous medium containing such a fracture. We consider a…

Numerical Analysis · Mathematics 2015-03-04 Thi-Thao-Phuong Hoang , Caroline Japhet , Michel Kern , Jean E. Roberts

This paper introduces a parallel and distributed extension to the alternating direction method of multipliers (ADMM) for solving convex problem: minimize $\sum_{i=1}^N f_i(x_i)$ subject to $\sum_{i=1}^N A_i x_i=c, x_i\in \mathcal{X}_i$. The…

Optimization and Control · Mathematics 2014-03-20 Wei Deng , Ming-Jun Lai , Zhimin Peng , Wotao Yin

This paper presents a strategy for a posteriori error estimation for substructured problems solved by non-overlapping domain decomposition methods. We focus on global estimates of the discretization error obtained through the error in…

Numerical Analysis · Mathematics 2012-09-03 Augustin Parret-Fréaud , Christian Rey , Pierre Gosselet , Frédéric Feyel

For a general third-order tensor $\mathcal{A}\in\mathbb{R}^{n\times n\times n}$ the paper studies two closely related problems, an SVD-like tensor decomposition and an (approximate) tensor diagonalization. We develop a Jacobi-type algorithm…

Numerical Analysis · Mathematics 2024-03-20 Erna Begovic

We prove convergence for the nonoverlapping Robin-Robin method applied to nonlinear elliptic equations with a $p$-structure, including degenerate diffusion equations governed by the $p$-Laplacian. This nonoverlapping domain decomposition is…

Numerical Analysis · Mathematics 2021-05-04 Emil Engström , Eskil Hansen

Non-negative matrix factorization (NMF) is a popular unsupervised learning approach widely used in image clustering. However, in real-world clustering scenarios, most existing NMF methods are highly sensitive to noise corruption and are…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Jingjing Liu , Nian Wu , Xianchao Xiu , Jianhua Zhang

Orthogonal systems in $\mathrm{L}_2(\mathbb{R})$, once implemented in spectral methods, enjoy a number of important advantages if their differentiation matrix is skew-symmetric and highly structured. Such systems, where the differentiation…

Numerical Analysis · Mathematics 2019-11-14 Arieh Iserles , Marcus Webb