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We introduce the tensor numerical method for solving optimal control problems that are constrained by fractional 2D and 3D elliptic operators with variable coefficients. We solve the governing equation for the control function which…

Numerical Analysis · Mathematics 2020-07-07 Britta Schmitt , Boris N. Khoromskij , Venera Khoromskaia , Volker Schulz

We present a novel enhanced cyclic coordinate descent (ECCD) framework for solving generalized linear models with elastic net constraints that reduces training time in comparison to existing state-of-the-art methods. We redesign the CD…

Machine Learning · Statistics 2025-10-24 Yixiao Wang , Zishan Shao , Ting Jiang , Aditya Devarakonda

We propose the Compact Coupling Interface Method (CCIM), a finite difference method capable of obtaining second-order accurate approximations of not only solution values but their gradients, for elliptic complex interface problems with…

Numerical Analysis · Mathematics 2024-06-21 Ray Zirui Zhang , Li-Tien Cheng

We continue our study [Domain Uncertainty Quantification in Computational Electromagnetics, JUQ (2020), 8:301--341] of the numerical approximation of time-harmonic electromagnetic fields for the Maxwell lossy cavity problem for uncertain…

Numerical Analysis · Mathematics 2022-12-15 Rubén Aylwin , Carlos Jerez-Hanckes , Christoph Schwab , Jakob Zech

We present a numerical method for solving the Poisson equation on a nested grid. The nested grid consists of uniform grids having different grid spacing and is designed to cover the space closer to the center with a finer grid. Thus our…

Astrophysics · Physics 2009-11-07 Tomoaki Matsumoto , Tomoyuki Hanawa

Accurate and robust correspondence matching is of utmost importance for various 3D computer vision tasks. However, traditional explicit programming-based methods often struggle to handle challenging scenarios, and deep learning-based…

Computer Vision and Pattern Recognition · Computer Science 2023-09-01 Chenbo Zhou , Shuai Su , Qijun Chen , Rui Fan

Bayesian inverse problems often involve sampling posterior distributions on infinite-dimensional function spaces. Traditional Markov chain Monte Carlo (MCMC) algorithms are characterized by deteriorating mixing times upon mesh-refinement,…

Computation · Statistics 2017-03-08 Alexandros Beskos , Mark Girolami , Shiwei Lan , Patrick E. Farrell , Andrew M. Stuart

This paper presents an efficient high-order sharp-interface method for solving the three-dimensional (3D) Poisson equation with Dirichlet boundary conditions on a nonuniform Cartesian grid with irregular domain boundaries. The new approach…

Computational Physics · Physics 2024-12-20 Shirzad Hosseinverdi , Hermann F. Fasel

Even though iterative solvers like the Conjugate Gradients method (CG) have been studied for over fifty years, fault tolerance for such solvers has seen much attention in recent years. For iterative solvers, two major reliable strategies of…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-17 Kiril Dichev , Dimitrios S. Nikolopoulos

The purpose of this article is to study extrapolation of solvability for boundary value problems of elliptic systems in divergence form on the upper half-space assuming De Giorgi type conditions. We develop a method allowing to treat each…

Classical Analysis and ODEs · Mathematics 2017-05-17 Pascal Auscher , Mihalis Mourgoglou

Extrapolation methods use the last few iterates of an optimization algorithm to produce a better estimate of the optimum. They were shown to achieve optimal convergence rates in a deterministic setting using simple gradient iterates. Here,…

Optimization and Control · Mathematics 2017-08-04 Damien Scieur , Alexandre d'Aspremont , Francis Bach

We propose a multiscale method for elliptic problems on complex domains, e.g. domains with cracks or complicated boundary. For local singularities this paper also offers a discrete alternative to enrichment techniques such as XFEM. We…

Numerical Analysis · Mathematics 2016-11-01 Daniel Elfverson , Mats G. Larson , Axel Målqvist

We introduce a novel Unsmoothed Aggregation (UA) Algebraic Multigrid (AMG) method combined with Preconditioned Conjugate Gradient (PCG) to overcome the limitations of Extended Position-Based Dynamics (XPBD) in high-resolution and…

Graphics · Computer Science 2025-05-20 Chunlei Li , Peng Yu , Tiantian Liu , Siyuan Yu , Yuting Xiao , Shuai Li , Aimin Hao , Yang Gao , Qinping Zhao

In this paper, we consider a class of finite-sum convex optimization problems whose objective function is given by the summation of $m$ ($\ge 1$) smooth components together with some other relatively simple terms. We first introduce a…

Optimization and Control · Mathematics 2015-10-27 Guanghui Lan , Yi Zhou

A self-learning algebraic multigrid method for dominant and minimal singular triplets and eigenpairs is described. The method consists of two multilevel phases. In the first, multiplicative phase (setup phase), tentative singular triplets…

Numerical Analysis · Mathematics 2011-02-07 Hans De Sterck

The paper suggests a preconditioning type method for fast solving of elliptic equations with oscillating quasiperiodic coefficients $A_\epsilon$ specified by the small parameter $\epsilon>0$. We use an iteration method generated by an…

Numerical Analysis · Mathematics 2015-10-02 Boris N. Khoromskij , Sergey I. Repin

A new finite difference method on irregular, locally perturbed rectangular grids has been developed for solving electromagnetic waves around curved perfect electric conductors (PEC). This method incorporates the back and forth error…

Numerical Analysis · Mathematics 2022-05-25 Haiyu Zou , Yingjie Liu

This paper develops a high-order selective discontinuous Galerkin (SDG) method for solving elliptic interface problems on interface-unfitted Cartesian meshes. This method applies the discontinuous Galerkin (DG) formulation on interface…

Numerical Analysis · Mathematics 2026-05-20 Fang Liu , Haroun Meghaichi , Xu Zhang

We propose a new algorithm for finite sum optimization which we call the curvature-aided incremental aggregated gradient (CIAG) method. Motivated by the problem of training a classifier for a d-dimensional problem, where the number of…

Machine Learning · Statistics 2017-10-26 Hoi-To Wai , Wei Shi , Angelia Nedic , Anna Scaglione

Column Generation (CG) is an effective and iterative algorithm to solve large-scale linear programs (LP). During each CG iteration, new columns are added to improve the solution of the LP. Typically, CG greedily selects one column with the…

Machine Learning · Computer Science 2024-12-30 Yi-Xiang Hu , Feng Wu , Shaoang Li , Yifang Zhao , Xiang-Yang Li
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