Publications related to Commuting matrices

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

Philadelphia2024

DIVIDE-AND-CONQUER METHODS FOR FUNCTIONS OF MATRICES WITH BANDED OR HIERARCHICAL LOW-RANK STRUCTURE\ast

Daniel Kressner, Stefano Massei, Alice Cortinovis

This work is concerned with approximating matrix functions for banded matrices, hierarchically semiseparable matrices, and related structures. We develop a new divide-and-conquer method based on (rational) Krylov subspace methods for performing low-rank up ...

SIAM PUBLICATIONS2022

The double exponential runtime is tight for 2-stage stochastic ILPs

Kim-Manuel Klein, Klaus Jansen, Alexandra Anna Lassota

We consider fundamental algorithmic number theoretic problems and their relation to a class of block structured Integer Linear Programs (ILPs) called 2-stage stochastic. A 2-stage stochastic ILP is an integer program of the form min{c(T)x vertical bar Ax = ...

SPRINGER HEIDELBERG2022

Kinetic Euclidean Distance Matrices

Martin Vetterli, Ivan Dokmanic, Puoya Tabaghi

Euclidean distance matrices (EDMs) are a major tool for localization from distances, with applications ranging from protein structure determination to global positioning and manifold learning. They are, however, static objects which serve to localize point ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Low-Rank Updates And A Divide-And-Conquer Method For Linear Matrix Equations

Daniel Kressner, Stefano Massei

Linear matrix equations, such as the Sylvester and Lyapunov equations, play an important role in various applications, including the stability analysis and dimensionality reduction of linear dynamical control systems and the solution of partial differentia ...

SIAM PUBLICATIONS2019

MATHICSE Technical Report : A fast spectral divide-and-conquer method for banded matrices

Daniel Kressner, Ana Susnjara

Based on the spectral divide-and-conquer algorithm by Nakatsukasa and Higham [SIAM J. Sci. Comput., 35(3):A1325{A1349, 2013], we propose a new algorithm for computing all the eigenvalues and eigenvectors of a symmetric banded matrix. For this purpose, we c ...

MATHICSE2018

Fast Computation Of Spectral Projectors Of Banded Matrices

Daniel Kressner, Ana Susnjara

We consider the approximate computation of spectral projectors for symmetric banded matrices. While this problem has received considerable attention, especially in the context of linear scaling electronic structure methods, the presence of small relative s ...

Siam Publications2017

MATHICSE Technical Report : Low-rank updates and a divideand- conquer method for linear matrix equations

Daniel Kressner, Stefano Massei

MATHICSE2017

MATHICSE Technical Report : Fast computation of spectral projectors of banded matrices

Daniel Kressner, Ana Susnjara

MATHICSE2016

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Commuting matrices

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

DIVIDE-AND-CONQUER METHODS FOR FUNCTIONS OF MATRICES WITH BANDED OR HIERARCHICAL LOW-RANK STRUCTURE\ast

The double exponential runtime is tight for 2-stage stochastic ILPs

Kinetic Euclidean Distance Matrices

Low-Rank Updates And A Divide-And-Conquer Method For Linear Matrix Equations

MATHICSE Technical Report : A fast spectral divide-and-conquer method for banded matrices

Fast hierarchical solvers for symmetric eigenvalue problems

Fast Computation Of Spectral Projectors Of Banded Matrices

MATHICSE Technical Report : Low-rank updates and a divideand- conquer method for linear matrix equations

MATHICSE Technical Report : Fast computation of spectral projectors of banded matrices

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Chat with Graph Search

Fast hierarchical solvers for symmetric eigenvalue problems

MATHICSE Technical Report : A fast spectral divide-and-conquer method for banded matrices

Fast Computation Of Spectral Projectors Of Banded Matrices

RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

Kinetic Euclidean Distance Matrices

The double exponential runtime is tight for 2-stage stochastic ILPs

MATHICSE Technical Report : Low-rank updates and a divideand- conquer method for linear matrix equations

Low-Rank Updates And A Divide-And-Conquer Method For Linear Matrix Equations

MATHICSE Technical Report : Fast computation of spectral projectors of banded matrices