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Federated Learning is a popular distributed learning paradigm in machine learning. Meanwhile, composition optimization is an effective hierarchical learning model, which appears in many machine learning applications such as meta learning…

Machine Learning · Computer Science 2023-03-31 Feihu Huang

We consider a randomised implementation of the finite element method (FEM) for elliptic partial differential equations on high-dimensional models. This is motivated by applications where model predictions are essential for real-time process…

Numerical Analysis · Mathematics 2019-07-30 Yue Wu , Dimitris Kamilis , Nick Polydorides

Vortex element methods are often used to efficiently simulate incompressible flows using Lagrangian techniques. Use of the FMM (Fast Multipole Method) allows considerable speed up of both velocity evaluation and vorticity evolution terms in…

Computational Physics · Physics 2015-06-03 Nail A. Gumerov , Ramani Duraiswami

Wireless mesh networks (WMNs) depend on the spatial distribution of nodes, which directly influences connectivity, routing efficiency, and overall network performance. Conventional models typically assume uniform or random node placement,…

Networking and Internet Architecture · Computer Science 2025-12-01 Marat Zaidyn , Sayat Akhtanov , Dana Turlykozhayeva , Symbat Temesheva , Almat Akhmetali , Alisher Skabylov , Nurzhan Ussipov

Permanent Magnet multipoles (PMM) are widely used in accelerators to either focus particle beams or confine plasma in ion sources. The real magnetic field created by PMM is calculated by magnetic field simulation software and then used in…

Accelerator Physics · Physics 2020-05-20 Thomas Thuillier , Thomas Andre , Jose-Antonio Mendez-Giono

We develop a transfer matrix formalism to visualize the framing of discrete piecewise linear curves in three dimensional space. Our approach is based on the concept of an intrinsically discrete curve, which enables us to more effectively…

Biomolecules · Quantitative Biology 2015-05-27 Shuangwei Hu , Martin Lundgren , Antti J. Niemi

The Laplace-Beltrami problem on closed surfaces embedded in three dimensions arises in many areas of physics, including molecular dynamics (surface diffusion), electromagnetics (harmonic vector fields), and fluid dynamics (vesicle…

Numerical Analysis · Mathematics 2023-05-12 Dhwanit Agarwal , Michael O'Neil , Manas Rachh

The Fast Multipole Method (FMM) computes pairwise interactions between particles with an efficiency that scales linearly with the number of particles. The method works by grouping particles based on their spatial distribution and…

Computational Physics · Physics 2025-08-05 He Zhang

Classification of functional data where observations are curves or trajectories poses unique challenges, particularly under severe class imbalance. Traditional Random Forest algorithms, while robust for tabular data, often fail to capture…

Machine Learning · Statistics 2025-12-10 Fahad Mostafa , Hafiz Khan

We propose a novel method to measure the fractal dimension of a submonolayer metal adatom system grown under conditions of limited diffusivity on a surface. The method is based on measuring the specular peak attenuation of He atoms…

chem-ph · Physics 2009-10-28 D. A. Hamburger , A. T. Yinnon , R. B. Gerber

In this paper we propose an enhanced version of the residual sub-sampling method (RSM) in [9] for adaptive interpolation by radial basis functions (RBFs). More precisely, we introduce in the context of sub-sampling methods a maximum profile…

Numerical Analysis · Mathematics 2022-03-29 R. Cavoretto A. De Rossi

We propose conformable Adomian decomposition method (CADM) for fractional partial differential equations (FPDEs). This method is a new Adomian decomposition method (ADM) based on conformable derivative operator (CDO) to solve FPDEs. At the…

General Mathematics · Mathematics 2017-04-11 Omer Acan , Dumitru Baleanu

This study introduces a physics-based machine learning framework for modeling both brittle and ductile fractures. Unlike physics-informed neural networks, which solve partial differential equations by embedding physical laws as soft…

Numerical Analysis · Mathematics 2025-02-14 Fadi Aldakheel , Elsayed S. Elsayed , Yousef Heider , Oliver Weeger

Markov Chain Monte Carlo (MCMC) sampling methods are widely used but often encounter either slow convergence or biased sampling when applied to multimodal high dimensional distributions. In this paper, we present a general framework of…

Computation · Statistics 2017-09-12 Ricky Fok , Aijun An , Xiaogang Wang

We propose high-order FDTD schemes based on the Correction Function Method (CFM) for Maxwell's interface problems with discontinuous coefficients and complex interfaces. The key idea of the CFM is to model the correction function near an…

Numerical Analysis · Mathematics 2022-03-11 Yann-Meing Law , Jean-Christophe Nave

This paper is devoted to the efficient numerical solution of the Helmholtz equation in a two- or three-dimensional rectangular domain with an absorbing boundary condition (ABC). The Helmholtz problem is discretized by standard bilinear and…

Numerical Analysis · Computer Science 2019-10-24 Jari Toivanen , Monika Wolfmayr

In this article we propose a new adaptive numerical quadrature procedure which includes both local subdivision of the integration domain, as well as local variation of the number of quadrature points employed on each subinterval. In this…

Numerical Analysis · Mathematics 2015-08-17 Paul Houston , Thomas P. Wihler

In this paper, a new fast and low complexity transform is introduced for orthogonal frequency division multiplexing (OFDM) wireless systems. The new transform combines the effects of fast complex-Walsh-Hadamard transform (CHT) and the fast…

Signal Processing · Electrical Eng. & Systems 2023-10-30 Said Boussakta , Mounir T. Hamood , Mohammed Sh. Ahmed

In this paper, we present a fast multipole method (FMM) for solving the two-dimensional Laplace equation in a half-plane with Robin boundary conditions. The method is based on a novel expansion theory for the reaction component of the…

Numerical Analysis · Mathematics 2025-07-30 Chunzhi Xiang , Bo Wang , Wenzhong Zhang , Wei Cai

Appropriately designing the proposal kernel of particle filters is an issue of significant importance, since a bad choice may lead to deterioration of the particle sample and, consequently, waste of computational power. In this paper we…

Methodology · Statistics 2012-10-12 J. Cornebise , E. Moulines , J. Olsson