Groups
Low-rank approximation replaces a big matrix with one that has far fewer degrees of freedom while preserving most of its action.
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.