Reduced rank approximation of matrices has hitherto been possible only by unweighted least squares. This paper presents iterative techniques for obtaining such approximations when weights are ...

Dynamical low-rank approximation (DLRA) methods have emerged as a powerful numerical framework for addressing the challenges posed by high-dimensional problems. By restricting the evolution of a ...

Structured low-rank approximation (SLRA) is a mathematical framework that seeks to approximate a given data matrix by another matrix of lower rank while preserving intrinsic structural properties.