3 citations · 8 across the 5 of their papers we have counts for
7 papers
An Efficient Nonlinear Acceleration method that Exploits Symmetry of the Hessian
Huan He, Shifan Zhao, Ziyuan Tang +3
Nonlinear acceleration methods are powerful techniques to speed up fixed-point iterations. However, many acceleration methods require storing a large number of previous iterates an…
parGeMSLR: A Parallel Multilevel Schur Complement Low-Rank Preconditioning and Solution Package for General Sparse Matrices
Tianshi Xu, Vassilis Kalantzis, Ruipeng Li +3
This paper discusses parGeMSLR, a C++/MPI software library for the solution of sparse systems of linear algebraic equations via preconditioned Krylov subspace methods in distribute…
Fast randomized non-Hermitian eigensolver based on rational filtering and matrix partitioning
Vassilis Kalantzis, Yuanzhe Xi, Lior Horesh
This paper describes a set of rational filtering algorithms to compute a few eigenvalues (and associated eigenvectors) of non-Hermitian matrix pencils. Our interest lies in computi…
Learning optimal multigrid smoothers via neural networks
Ru Huang, Ruipeng Li, Yuanzhe Xi
Multigrid methods are one of the most efficient techniques for solving linear systems arising from Partial Differential Equations (PDEs) and graph Laplacians from machine learning…
Generating a Doppelganger Graph: Resembling but Distinct
Yuliang Ji, Ru Huang, Jie Chen +1
Deep generative models, since their inception, have become increasingly more capable of generating novel and perceptually realistic signals (e.g., images and sound waves). With the…
A power Schur complement Low-Rank correction preconditioner for general sparse linear systems
Qingqing Zheng, Yuanzhe Xi, Yousef Saad
An effective power based parallel preconditioner is proposed for general large sparse linear systems. The preconditioner combines a power series expansion method with some low-rank…