Matrix factorization techniques have become pivotal in data mining, enabling the extraction of latent structures from large-scale data matrices. These methods decompose complex datasets into ...

Nonnegative Matrix Factorization (NMF) has emerged as a powerful tool in data analysis, particularly noted for its ability to produce parts‐based, interpretable representations from high-dimensional ...

In statistical practice, rectangular tables of numeric data are commonplace, and are often analyzed using dimension-reduction methods like the singular value decomposition and its close cousin, ...

SIAM Journal on Applied Mathematics, Vol. 30, No. 4 (Jun., 1976), pp. 732-738 (7 pages) The explicit Wiener-Hopf factorization of the dispersion matrix Λ(z) is obtained for two scattering models which ...