8 citations · 23 across the 10 of their papers we have counts for
27 papers
The Refined Joint Bidiagonalization Method and an Implicitly Restarted Algorithm for Large GSVD Computations
Kaixiao Fang, Zhongxiao Jia
We make a convergence analysis on the joint bidiagonalization (JBD) method that computes several extreme generalized singular value decomposition (GSVD) components of a regular mat…
A Numerical Analysis of Sketched Linear Squares Problems and Stopping Criteria for Iterative Solvers
Zhongxiao Jia, Xinyuan Wan
Randomized subspace embedding methods have had a great impact on the solution of a linear least squares (LS) problem by reducing its row dimension, leading to a randomized or sketc…
A Chebyshev--Jackson series based block SS--RR algorithm for computing partial eigenpairs of real symmetric matrices
Zhongxiao Jia, Tianhang Liu
This paper considers eigenpair computations of large symmetric matrices with the desired eigenvalues lying in a given interval using the contour integral-based block SS--RR method,…
An Implicitly Restarted Joint Bidiagonalization Algorithm for Large GSVD Computations
Kaixiao Fang, Zhongxiao Jia
The joint bidiagonalization (JBD) process of a regular matrix pair is mathematically equivalent to two simultaneous Lanczos bidiagonalization processes of the upper and l…
A CJ-FEAST GSVDsolver for computing a partial GSVD of a large matrix pair with the generalized singular values in a given interval
Zhongxiao Jia, Kailiang Zhang
We propose a CJ-FEAST GSVDsolver to compute a partial generalized singular value decomposition (GSVD) of a large matrix pair with the generalized singular values in a given…
An augmented matrix-based CJ-FEAST SVDsolver for computing a partial singular value decomposition with the singular values in a given interval
Zhongxiao Jia, Kailiang Zhang
The cross-product matrix-based CJ-FEAST SVDsolver proposed previously by the authors is shown to compute the left singular vector possibly much less accurately than the right singu…