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Recently, Nystr\"{o}m method has proved its prominence empirically and theoretically in speeding up the training of kernel machines while retaining satisfactory performances and accuracy. So far, there are several different approaches…

Machine Learning · Computer Science 2021-09-21 Weida Li , Mingxia Liu , Daoqiang Zhang

We present a method for computing nearly singular integrals that occur when single or double layer surface integrals, for harmonic potentials or Stokes flow, are evaluated at points nearby. Such values could be needed in solving an integral…

Numerical Analysis · Mathematics 2024-06-21 J. Thomas Beale , Svetlana Tlupova

Kernel $k$-means clustering can correctly identify and extract a far more varied collection of cluster structures than the linear $k$-means clustering algorithm. However, kernel $k$-means clustering is computationally expensive when the…

Machine Learning · Computer Science 2019-02-12 Shusen Wang , Alex Gittens , Michael W. Mahoney

This paper extends and analyzes the high-order kernel regularization framework of Beale & Tlupova (arXiv:2510.13639) to all four on-surface boundary integral operators of the Helmholtz Calderon calculus in three dimensions: the…

Numerical Analysis · Mathematics 2026-04-29 Luiz M. Faria , Carlos Perez-Arancibia , Svetlana Tlupova

In this paper, we study the Nystr{\"o}m type subsampling for large scale kernel methods to reduce the computational complexities of big data. We discuss the multi-penalty regularization scheme based on Nystr{\"o}m type subsampling which is…

Machine Learning · Statistics 2024-04-09 Abhishake Rastogi , Sivananthan Sampath

This paper presents smoothed combined field integral equations for the solution of Dirichlet and Neumann exterior Helmholtz problems. The integral equations introduced in this paper are smooth in the sense that they only involve…

Numerical Analysis · Mathematics 2017-01-16 Carlos Pérez-Arancibia

Kernel methods have achieved very good performance on large scale regression and classification problems, by using the Nystr\"om method and preconditioning techniques. The Nystr\"om approximation -- based on a subset of landmarks -- gives a…

Machine Learning · Computer Science 2020-02-21 Michaël Fanuel , Joachim Schreurs , Johan A. K. Suykens

We give a detailed general description of a recent geometrical discretisation scheme and illustrate, by explicit numerical calculation, the scheme's ability to capture topological features. The scheme is applied to the Abelian Chern-Simons…

High Energy Physics - Theory · Physics 2009-10-31 Samik Sen , Siddhartha Sen , James C. Sexton , David H. Adams

Over the last two decades, several fast, robust, and high-order accurate methods have been developed for solving the Poisson equation in complicated geometry using potential theory. In this approach, rather than discretizing the partial…

Numerical Analysis · Mathematics 2024-09-19 Fredrik Fryklund , Leslie Greengard , Shidong Jiang , Samuel Potter

We present a regularization strategy that leads to well-conditioned boundary integral equation formulations of Helmholtz equations with impedance boundary conditions in two-dimensional Lipschitz domains. We consider both the case of…

Numerical Analysis · Mathematics 2016-07-05 Catalin Turc , Yassine Boubendir , Mohamed Kamel Riahi

We consider a numerical scheme for Hamilton-Jacobi equations based on a direct discretization of the Lax-Oleinik semi-group. We prove that this method is convergent with respect to the time and space stepsizes provided the solution is…

Numerical Analysis · Mathematics 2013-12-06 Anne Bouillard , Erwan Faou , Maxime Zavidovique

Asymmetric data naturally exist in real life, such as directed graphs. Different from the common kernel methods requiring Mercer kernels, this paper tackles the asymmetric kernel-based learning problem. We describe a nonlinear extension of…

Machine Learning · Computer Science 2023-06-13 Qinghua Tao , Francesco Tonin , Panagiotis Patrinos , Johan A. K. Suykens

A framework is developed for a robust and highly accurate numerical solution of the coupled Stokes-Darcy system in three dimensions. The domain decomposition method is based on a Dirichlet-Neumann type splitting of the interface conditions…

Numerical Analysis · Mathematics 2022-01-19 Svetlana Tlupova

We propose KROM, a kernel-based reduced-order framework for fast solution of nonlinear partial differential equations. KROM formulates PDE solution as a minimum-norm (Gaussian-process) recovery problem in an RKHS, and accelerates the…

Numerical Analysis · Mathematics 2026-03-03 Aras Bacho , Jonghyeon Lee , Houman Owhadi

Direct numerical solution of the coordinate-space integral-equation version of the two-particle Lippmann Schwinger (LS) equation is considered as a means of avoiding the shortcomings of partial-wave expansion at high energies and in the…

Computational Physics · Physics 2016-11-15 Zeki C. Kuruoglu

A crucial part of successful wave propagation related inverse problems is an efficient and accurate numerical scheme for solving the seismic wave equations. In particular, the numerical solution to a multi-dimensional Helmholtz equation can…

Numerical Analysis · Mathematics 2021-03-11 Hatef Dastour , Wenyuan Liao

We present a general purpose method for solving partial differential equations on a closed surface, based on a technique for discretizing the surface introduced by Wenjun Ying and Wei-Cheng Wang [J. Comput. Phys. 252 (2013), pp. 606-624]…

Numerical Analysis · Mathematics 2020-04-21 J. Thomas Beale

Several problems in magnetically confined fusion, such as the computation of exterior vacuum fields or the decomposition of the total magnetic field into separate contributions from the plasma and the external sources, are best formulated…

Numerical Analysis · Mathematics 2019-11-25 Dhairya Malhotra , Antoine J. Cerfon , Michael O'Neil , Evan Toler

We present a finite element scheme for fractional diffusion problems with varying diffusivity and fractional order. We consider a symmetric integral form of these nonlocal equations defined on general geometries and in arbitrary bounded…

Numerical Analysis · Mathematics 2023-06-28 Wenyu Lei , George Turkiyyah , Omar Knio

In the present work, we investigate the computational efficiency afforded by higher-order finite-element discretization of the saddle-point formulation of orbital-free density functional theory. We first investigate the robustness of viable…

Computational Physics · Physics 2015-05-30 Phani Motamarri , Mrinal Iyer , Jaroslaw Knap , Vikram Gavini
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