Conference paper
Generative Adversarial Symmetry Discovery
Jianke Yang, Robin Walters, et al.
ICML 2023
Inverse iteration is widely used to compute the eigenvectors of a matrix once accurate eigenvalues are known. We discuss various issues involved in any implementation of inverse iteration for real, symmetric matrices. Current implementations resort to reorthogonalization when eigenvalues agree to more than three digits relative to the norm. Such reorthogonalization can have unexpected consequences. Indeed, as we show in this paper, the implementations in EISPACK and LAPACK may fail. We illustrate with both theoretical and empirical failures.
Jianke Yang, Robin Walters, et al.
ICML 2023
Charles A Micchelli
Journal of Approximation Theory
Amir Ali Ahmadi, Raphaël M. Jungers, et al.
SICON
Chai Wah Wu
Linear Algebra and Its Applications