Efficient Preconditioning of Hp-Fem Matrices by Hierarchical Low-Rank Approximations

Journal of Scientific Computing - United States
doi 10.1007/s10915-016-0347-x
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Springer Science and Business Media LLC

Related search

On the Compression of Low Rank Matrices

SIAM Journal of Scientific Computing
Computational MathematicsApplied Mathematics
2005English

Frequency-Limited Balanced Truncation With Low-Rank Approximations

SIAM Journal of Scientific Computing
Computational MathematicsApplied Mathematics
2016English

Budget-Optimal Crowdsourcing Using Low-Rank Matrix Approximations

2011English

Why Are Big Data Matrices Approximately Low Rank?

SIAM Journal on Mathematics of Data Science
2019English

Recovery of Low-Rank Matrices Under Affine Constraints via a Smoothed Rank Function

IEEE Transactions on Signal Processing
Electronic EngineeringSignal ProcessingElectrical
2014English

Combinatorial Conditions for the Unique Completability of Low-Rank Matrices

SIAM Journal on Discrete Mathematics
Mathematics
2014English

The Inertia of the Symmetric Approximation for Low-Rank Matrices

Linear and Multilinear Algebra
Number TheoryAlgebra
2017English

Addressing High Dimensionality in Reliability Analysis Using Low-Rank Tensor Approximations

2015English

QR Factorization of Block Low-Rank Matrices With Weak Admissibility Condition

Journal of Information Processing
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy