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A finite element method for elliptic problems with discontinuous coefficients is presented. The discontinuity is assumed to take place along a closed smooth curve. The proposed method allows to deal with meshes that are not adapted to the…

Numerical Analysis · Mathematics 2007-07-12 Gunther H. Peichl , Rachid Touzani

Sketching is a probabilistic data compression technique that has been largely developed in the computer science community. Numerical operations on big datasets can be intolerably slow; sketching algorithms address this issue by generating a…

Methodology · Statistics 2019-04-04 Daniel Ahfock , William J. Astle , Sylvia Richardson

This paper develops and analyzes an efficient numerical method for solving elliptic partial differential equations, where the diffusion coefficients are random perturbations of deterministic diffusion coefficients. The method is based upon…

Numerical Analysis · Mathematics 2016-03-30 X. Feng , J. Lin. , C. Lorton

New finite element methods are proposed for elliptic interface problems in one and two dimensions. The main motivation is not only to get an accurate solution but also an accurate first order derivative at the interface (from each side).…

Numerical Analysis · Mathematics 2017-03-02 Fangfang Qin , Zhaohui Wang , Zhijie Ma , Zhilin Li

We propose a novel numerical algorithm utilizing model reduction for computing solutions to stationary partial differential equations involving the spectral fractional Laplacian. Our approach utilizes a known characterization of the…

Numerical Analysis · Mathematics 2019-04-23 Huy Dinh , Harbir Antil , Yanlai Chen , Elena Cherkaev , Akil Narayan

We propose a new nonconforming finite element algorithm to approximate the solution to the elliptic problem involving the fractional Laplacian. We first derive an integral representation of the bilinear form corresponding to the variational…

Numerical Analysis · Mathematics 2018-12-20 Andrea Bonito , Wenyu Lei , Joseph E. Pasciak

We consider distributed convex optimization problems that involve a separable objective function and nontrivial functional constraints, such as Linear Matrix Inequalities (LMIs). We propose a decentralized and computationally inexpensive…

Optimization and Control · Mathematics 2018-01-22 Soomin Lee , Michael M. Zavlanos

We consider the problem of recovering an $n_1 \times n_2$ low-rank matrix with $k$-sparse singular vectors from a small number of linear measurements (sketch). We propose a sketching scheme and an algorithm that can recover the singular…

Information Theory · Computer Science 2024-07-02 Xiaoqi Liu , Ramji Venkataramanan

We explore the connection between fractional order partial differential equations in two or more spatial dimensions with boundary integral operators to develop techniques that enable one to efficiently tackle the integral fractional…

Numerical Analysis · Mathematics 2019-05-27 Mark Ainsworth , Christian Glusa

Kernel methods are learning algorithms that enjoy solid theoretical foundations while suffering from important computational limitations. Sketching, which consists in looking for solutions among a subspace of reduced dimension, is a well…

Machine Learning · Statistics 2023-11-07 Tamim El Ahmad , Pierre Laforgue , Florence d'Alché-Buc

In this work we propose an efficient and accurate multi-scale optical simulation algorithm by applying a numerical version of slowly varying envelope approximation in FEM. Specifically, we employ the fast iterative method to quickly compute…

Optics · Physics 2024-12-03 Fan Xiao , Jingwei Wang , Zhongfei Xiong , Yuntian Chen

Multiple scale homogenization problems are reduced to single scale problems in higher dimension. It is shown that sparse tensor product Finite Element Methods (FEM) allow the numerical solution in complexity independent of the dimension and…

Numerical Analysis · Mathematics 2025-10-20 Christoph Schwab

In this paper, authors shall introduce a finite element method by using a weakly defined gradient operator over discontinuous functions with heterogeneous properties. The use of weak gradients and their approximations results in a new…

Numerical Analysis · Mathematics 2012-11-14 Junping Wang , Xiu Ye

In this work we focus on two different methods to deal with parametrized partial differential equations in an efficient and accurate way. Starting from high fidelity approximations built via the hierarchical model reduction discretization,…

Numerical Analysis · Mathematics 2023-08-08 Matteo Zancanaro , Francesco Ballarin , Simona Perotto , Gianluigi Rozza

This paper discusses predictive inference and feature selection for generalized linear models with scarce but high-dimensional data. We argue that in many cases one can benefit from a decision theoretically justified two-stage approach:…

Machine Learning · Statistics 2020-11-09 Juho Piironen , Markus Paasiniemi , Aki Vehtari

A general method for accelerating fixed point schemes for problems related to partial differential equations is presented in this article. The speedup is obtained by training a reduced-order model on-the-fly, removing the need to do an…

Numerical Analysis · Mathematics 2025-12-01 Philippe-André Luneau , Jean Deteix

In the present work we introduce a novel refinement algorithm for two-dimensional elliptic partial differential equations discretized with Virtual Element Method (VEM). The algorithm improves the numerical solution accuracy and the mesh…

Numerical Analysis · Mathematics 2024-03-18 Stefano Berrone , Fabio Vicini

In this paper, we propose a novel adaptive finite element method for an elliptic equation with line Dirac delta functions as a source term. We first study the well-posedness and global regularity of the solution in the whole domain. Instead…

Numerical Analysis · Mathematics 2022-07-12 Huihui Cao , Hengguang Li , Nianyu Yi , Peimeng Yin

We present a new method for stochastic shape optimisation of engineering structures. The method generalises an existing deterministic scheme, in which the structure is represented and evolved by a level-set method coupled with mathematical…

Statistical Mechanics · Physics 2017-09-13 Lester O. Hedges , H. Alicia Kim , Robert L. Jack

This work is concerned with quasi-optimal a-priori finite element error estimates for the obstacle problem in the $L^2$-norm. The discrete approximations are introduced as solutions to a finite element discretization of an accordingly…

Numerical Analysis · Mathematics 2018-11-26 Dominik Hafemeyer , Christian Kahle , Johannes Pfefferer