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This paper develops a new class of algorithms for general linear systems and eigenvalue problems. These algorithms apply fast randomized sketching to accelerate subspace projection methods, such as GMRES and Rayleigh--Ritz. This approach…

Numerical Analysis · Mathematics 2022-02-17 Yuji Nakatsukasa , Joel A. Tropp

Mixed-precision arithmetic offers significant computational advantages for large-scale matrix computation tasks, yet preserving accuracy and stability in eigenvalue problems and the singular value decomposition (SVD) remains challenging.…

Numerical Analysis · Mathematics 2025-05-05 Tianshi Xu , Zechen Zhang , Jie Chen , Yousef Saad , Yuanzhe Xi

We discuss the spectral subspace perturbation problem for a self-adjoint operator. Assuming that the convex hull of a part of its spectrum does not intersect the remainder of the spectrum, we establish an \textit{a priori} sharp bound on…

Spectral Theory · Mathematics 2007-05-23 Alexander K. Motovilov , Alexei V. Selin

A method is presented for obtaining rigorous error estimates for approximate solutions of the Riccati equation, with real or complex potentials. Our main tool is to derive invariant region estimates for complex solutions of the Riccati…

Mathematical Physics · Physics 2010-08-18 Felix Finster , Joel Smoller

This work deals with approximate solution of generalized eigenvalue problem with coefficient matrix that is an affine function of d-parameters. The coefficient matrix is assumed to be symmetric positive definite and spectrally equivalent to…

Numerical Analysis · Mathematics 2025-03-12 Joanna Bisch , Antti Hannukainen

In statistics and machine learning, people are often interested in the eigenvectors (or singular vectors) of certain matrices (e.g. covariance matrices, data matrices, etc). However, those matrices are usually perturbed by noises or…

Statistics Theory · Mathematics 2017-06-05 Jianqing Fan , Weichen Wang , Yiqiao Zhong

Under the hypothesis that the deviations of the desired eigenvectors of the matrix $A$ from the underlying subspace tend to zero, the Ritz vectors may not converge and have poor or little accuracy. This phenomenon is not unusual and…

Numerical Analysis · Mathematics 2026-05-14 Zhongxiao Jia , Tianhang Liu

The absolute change in the Rayleigh quotient (RQ) is bounded in this paper in terms of the norm of the residual and the change in the vector. If $x$ is an eigenvector of a self-adjoint bounded operator $A$ in a Hilbert space, then the RQ of…

Numerical Analysis · Mathematics 2016-10-20 Peizhen Zhu , Merico E. Argentati , Andrew V. Knyazev

A lower semi-definite self-adjoint linear operator in a Hilbert space is taken whose discrete spectrum is not empty and comprises at least several eigenvalues $\lambda_{min}=\lambda_1\leqslant\ldots\leqslant\lambda_m<\sigma_{ess}$. The…

Spectral Theory · Mathematics 2019-02-19 Ruslan Sharipov

Eigenvalue estimates that are optimal in some sense have self-evident appeal and leave estimators with a sense of virtue and economy. So, it is natural that ongoing searches for effective strategies for difficult tasks such as estimating…

Rings and Algebras · Mathematics 2007-05-23 Christopher Beattie

We consider bounds on the convergence of Ritz values from a sequence of Krylov subspaces to interior eigenvalues of Hermitean matrices. These bounds are useful in regions of low spectral density, for example near voids in the spectrum, as…

Numerical Analysis · Mathematics 2011-10-18 Chris Johnson , A. D. Kennedy

Computing the top eigenvectors of a matrix is a problem of fundamental interest to various fields. While the majority of the literature has focused on analyzing the reconstruction error of low-rank matrices associated with the retrieved…

Machine Learning · Computer Science 2022-02-17 Ruo-Chun Tzeng , Po-An Wang , Florian Adriaens , Aristides Gionis , Chi-Jen Lu

In this paper we provide a priori error estimates in standard Sobolev (semi-)norms for approximation in spline spaces of maximal smoothness on arbitrary grids. The error estimates are expressed in terms of a power of the maximal grid…

Numerical Analysis · Mathematics 2019-07-09 Espen Sande , Carla Manni , Hendrik Speleers

This note presents sharp inequalities for deviation probability of a general quadratic form of a random vector \(\xiv\) with finite exponential moments. The obtained deviation bounds are similar to the case of a Gaussian random vector. The…

Probability · Mathematics 2013-02-08 Vladimir Spokoiny

An efficient Jacobi-Galerkin spectral method for calculating eigenvalues of Riesz fractional partial differential equations with homogeneous Dirichlet boundary values is proposed in this paper. In order to retain the symmetry and positive…

Numerical Analysis · Mathematics 2018-03-12 Lizhen Chen , Zhiping Mao , Huiyuan Li

We define angles from-to and between infinite dimensional subspaces of a Hilbert space, inspired by the work of E. J. Hannan, 1961/1962 for general canonical correlations of stochastic processes. The spectral theory of selfadjoint operators…

Numerical Analysis · Mathematics 2010-07-02 Andrew Knyazev , Abram Jujunashvili , Merico Argentati

We obtain explicit error bounds for the $d$-dimensional normal approximation on hyperrectangles for a random vector that has a Stein kernel, or admits an exchangeable pair coupling, or is a non-linear statistic of independent random…

Probability · Mathematics 2020-09-08 Xiao Fang , Yuta Koike

In this paper, we study the deep Ritz method for solving the linear elasticity equation from a numerical analysis perspective. A modified Ritz formulation using the $H^{1/2}(\Gamma_D)$ norm is introduced and analyzed for linear elasticity…

Numerical Analysis · Mathematics 2023-08-02 Min Liu , Zhiqiang Cai , Karthik Ramani

This paper presents a posteriori error estimates for conforming numerical approximations of eigenvalue clusters of second-order self-adjoint elliptic linear operators with compact resolvent. Given a cluster of eigenvalues, we estimate the…

Numerical Analysis · Mathematics 2020-08-11 Eric Cancès , Geneviève Dusson , Yvon Maday , Benjamin Stamm , Martin Vohralík

We prove asymptotically optimal upper bounds for the eigenvalues of the Wentzel-Laplace operator on Riemannian manifolds with Ricci curvature bounded below. These bounds depend highly on the geometry of the boundary in addition to the…

Metric Geometry · Mathematics 2020-06-23 Aïssatou M. Ndiaye