Complex moment-based supervised eigenmap for dimensionality reduction
Dimensionality reduction methods that project highdimensional data to a low-dimensional
space by matrix trace optimization are widely used for clustering and classification. The …
space by matrix trace optimization are widely used for clustering and classification. The …
Spectral discretization errors in filtered subspace iteration
J Gopalakrishnan, L Grubišić, J Ovall - Mathematics of computation, 2020 - ams.org
We consider filtered subspace iteration for approximating a cluster of eigenvalues (and its
associated eigenspace) of a (possibly unbounded) selfadjoint operator in a Hilbert space …
associated eigenspace) of a (possibly unbounded) selfadjoint operator in a Hilbert space …
A FEAST SVDsolver based on Chebyshev–Jackson series for computing partial singular triplets of large matrices
Z Jia, K Zhang - Journal of Scientific Computing, 2023 - Springer
The FEAST eigensolver is extended to the computation of the singular triplets of a large
matrix A with the singular values in a given interval. The resulting FEAST SVDsolver is …
matrix A with the singular values in a given interval. The resulting FEAST SVDsolver is …
Block Krylov-type complex moment-based eigensolvers for solving generalized eigenvalue problems
Complex moment-based eigensolvers for solving interior eigenvalue problems have been
studied because of their high parallel efficiency. Recently, we proposed the block Arnoldi …
studied because of their high parallel efficiency. Recently, we proposed the block Arnoldi …
Block SS–CAA: a complex moment-based parallel nonlinear eigensolver using the block communication-avoiding Arnoldi procedure
Complex moment-based parallel eigensolvers have been actively studied owing to their
high parallel efficiency. In this paper, we propose a block SS–CAA method, which is a …
high parallel efficiency. In this paper, we propose a block SS–CAA method, which is a …
[HTML][HTML] Complex moment-based eigensolver coupled with two Krylov subspaces
Complex moment-based eigensolvers have been well studied for solving interior eigenvalue
problems because of their high parallel efficiency. Recently, as a time-efficient complex …
problems because of their high parallel efficiency. Recently, as a time-efficient complex …
Scalable eigen-analysis engine for large-scale eigenvalue problems
Our project aims to develop a massively parallel Eigen-Supercomputing Engine for post-
petascale systems. Our Eigen-Engines are based on newly designed algorithms that are …
petascale systems. Our Eigen-Engines are based on newly designed algorithms that are …
Efficient and scalable calculation of complex band structure using Sakurai-Sugiura method
Complex band structures (CBSs) are useful to characterize the static and dynamical
electronic properties of materials. Despite the intensive developments, the first-principles …
electronic properties of materials. Despite the intensive developments, the first-principles …
A CJ-FEAST GSVDsolver for computing a partial GSVD of a large matrix pair with the generalized singular values in a given interval
Z Jia, K Zhang - arXiv preprint arXiv:2310.10146, 2023 - arxiv.org
We propose a CJ-FEAST GSVDsolver to compute a partial generalized singular value
decomposition (GSVD) of a large matrix pair $(A, B) $ with the generalized singular values …
decomposition (GSVD) of a large matrix pair $(A, B) $ with the generalized singular values …
Solving Maxwell's eigenvalue problem via isogeometric boundary elements and a contour integral method
arXiv:2001.09686v2 [cs.CE] 8 Jun 2020 Page 1 Solving Maxwell’s Eigenvalue Problem via
Isogeometric Boundary Elements and a Contour Integral Method Stefan Kurza, Sebastian …
Isogeometric Boundary Elements and a Contour Integral Method Stefan Kurza, Sebastian …