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Author

S. Sathyapriya

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Open access Sep 2026

Matrix Factorization Techniques in Data Science

Matrix factorization is an important mathematical technique used in data science to represent large and complex datasets in a lower-dimensional form. The fundamental idea is to decompose a matrix into two or more matrices whose product approximates or reconstructs the original data matrix. Techniques such as Singular V...

S. Sathyapriya · 0 citations
Review Open access Jul 2026

Linear Algebraic Framework of Quantum State Representation

Linear algebra provides the mathematical foundation of quantum mechanics by rep-resenting physical states as vectors in complex Hilbert spaces and observables as linear operators. The concepts of vector spaces, basis, orthogonality, inner products, and matrix transformations enable a rigorous description of quantum sys...

S. Sathyapriya · 0 citations

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