A Riemannian inexact Newton‐CG method for stochastic inverse singular value problems
Ru-ru Ma, Zheng‐Jian Bai · Numerical Linear Algebra with Applications · 2020
Summary In this article, we consider the stochastic inverse singular value problem (ISVP) of constructing a stochastic matrix from the prescribed realizable singular values. We propose a Riemannian inexact Newton‐CG method with various choices of forcing terms for solving the stochastic ISVP. We show the proposed method converges linearly or superlinearly for different forcing terms under some assumptions. We also extend the proposed method to the case of prescribed entries. Finally, we report some numerical results to demonstrate the effectiveness of the proposed method. MOS SUBJECT CLASSIFICATION 65F18; 65F15; 15A18; 65K05; 90C26; 90C48