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We consider the approximation of elliptic eigenvalue problem with an immersed interface. The main aim of this paper is to prove the stability and convergence of an immersed finite element method (IFEM) for eigenvalues using Crouzeix-Raviart…

Numerical Analysis · Mathematics 2014-12-11 Seungwoo Lee , Do Y. Kwak , Imbo Sim

The convergence property of a stochastic algorithm for the self-consistent field (SCF) calculations of electron structures is studied. The algorithm is formulated by rewriting the electron charges as a trace/diagonal of a matrix function,…

Numerical Analysis · Mathematics 2023-04-20 Taehee Ko , Xiantao Li

Unsupervised feature extraction algorithms form one of the most important building blocks in machine learning systems. These algorithms are often adapted to the event-based domain to perform online learning in neuromorphic hardware.…

Neural and Evolutionary Computing · Computer Science 2019-07-31 Saeed Afshar , Ying Xu , Jonathan Tapson , André van Schaik , Gregory Cohen

In this paper, we present and analyze a new set of low-rank recovery algorithms for linear inverse problems within the class of hard thresholding methods. We provide strategies on how to set up these algorithms via basic ingredients for…

Numerical Analysis · Computer Science 2013-01-15 Anastasios Kyrillidis , Volkan Cevher

Finite-element (FE) discretisations have emerged as a powerful real-space alternative to large-scale Kohn-Sham density functional theory (DFT) calculations, offering systematic convergence, excellent parallel scalability, while…

Computational Physics · Physics 2025-12-11 Gourab Panigrahi , Phani Motamarri

Iterative multiscale methods for electronic structure calculations offer several advantages for large-scale problems. Here we examine a nonlinear full approximation scheme (FAS) multigrid method for solving fixed potential and…

Materials Science · Physics 2007-05-23 Nimal Wijesekera , Guogang Feng , Thomas L. Beck

In this paper we develop randomized Krylov subspace methods for efficiently computing regularized solutions to large-scale linear inverse problems. Building on the recently developed randomized Gram-Schmidt process, where sketched inner…

Numerical Analysis · Mathematics 2025-08-29 Julianne Chung , Silvia Gazzola

Due to the vast number of students enrolled in programming courses, there has been an increasing number of automated program repair techniques focused on introductory programming assignments (IPAs). Typically, such techniques use program…

Software Engineering · Computer Science 2025-05-01 Pedro Orvalho , Mikoláš Janota , Vasco Manquinho

Stencil computations are widely used to simulate the change of state of physical systems across a multidimensional grid over multiple timesteps. The state-of-the-art techniques in this area fall into three groups: cache-aware tiled looping…

Data Structures and Algorithms · Computer Science 2021-05-17 Zafar Ahmad , Rezaul Chowdhury , Rathish Das , Pramod Ganapathi , Aaron Gregory , Yimin Zhu

This paper proposes an efficient algorithm for solving the Hartree--Fock equation combining a multilevel correction scheme with an adaptive refinement technique to improve computational efficiency. The algorithm integrates a multilevel…

Numerical Analysis · Mathematics 2025-10-14 Fei Xu

The parallel full approximation scheme in space and time (PFASST) introduced by Emmett and Minion in 2012 is an iterative strategy for the temporal parallelization of ODEs and discretized PDEs. As the name suggests, PFASST is similar in…

Numerical Analysis · Mathematics 2015-11-17 Michael Minion , Robert Speck , Matthias Bolten , Matthew Emmett , Daniel Ruprecht

A fast algorithm for inverse Cholesky factorization is proposed, to compute a triangular square-root of the estimation error covariance matrix for Vertical Bell Laboratories Layered Space-Time architecture (V-BLAST). It is then applied to…

Signal Processing · Electrical Eng. & Systems 2020-04-02 Hufei Zhu , Wen Chen , Bin Li , Feifei Gao

It is needed to solve generalized eigenvalue problems (GEP) in many applications, such as the numerical simulation of vibration analysis, quantum mechanics, electronic structure, etc. The subspace iteration is a kind of widely used…

Numerical Analysis · Mathematics 2023-01-02 Biyi Wang , Hengbin An , Hehu Xie , Zeyao Mo

Enlarged Krylov subspace methods and their s-step versions were introduced [7] in the aim of reducing communication when solving systems of linear equations Ax = b. These enlarged CG methods consist of enlarging the Krylov subspace by a…

Numerical Analysis · Mathematics 2024-09-18 Sophie M. Moufawad

Subspace recycling iterative methods and other subspace augmentation schemes are a successful extension to Krylov subspace methods in which a Krylov subspace is augmented with a fixed subspace spanned by vectors deemed to be helpful in…

Numerical Analysis · Mathematics 2022-02-11 Kirk M. Soodhalter

We propose a penalized likelihood framework for estimating multiple precision matrices from different classes. Most existing methods either incorporate no information on relationships between the precision matrices, or require this…

Machine Learning · Statistics 2020-03-03 Bradley S. Price , Aaron J. Molstad , Ben Sherwood

Solving symmetric positive definite linear problems is a fundamental computational task in machine learning. The exact solution, famously, is cubicly expensive in the size of the matrix. To alleviate this problem, several linear-time…

Machine Learning · Computer Science 2017-06-02 Filip de Roos , Philipp Hennig

It is classical that, when the small deformation is assumed, the incremental analysis problem of an elastoplastic structure with a piecewise-linear yield condition and a linear strain hardening model can be formulated as a convex quadratic…

Optimization and Control · Mathematics 2017-08-22 Yoshihiro Kanno

Modern data-driven applications require that databases support fast cross-model analytical queries. Achieving fast analytical queries in a database system is challenging since they are usually scan-intensive (i.e., they need to intensively…

Databases · Computer Science 2023-09-22 Jianfeng Huang , Dongjing Miao , Xin Liu

The work of Wachter and Biegler suggests that infeasible-start interior point methods (IPMs) developed for linear programming cannot be adapted to nonlinear optimization without significant modification, i.e., using a two-phase or penalty…

Optimization and Control · Mathematics 2018-01-12 Oliver Hinder , Yinyu Ye
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