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.

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Numerical computation and mathematical software form the backbone of modern scientific inquiry, facilitating the approximation of real numbers, the solution of complex mathematical models, and the ...