Groups
Singular Value Decomposition (SVD) factors any m×n matrix A into A = UΣV^{T}, where U and V are orthogonal and Σ is diagonal with nonnegative entries.
Linear algebra studies vectors, linear combinations, and transformations that preserve addition and scalar multiplication.