SVD

Singular Value Decomposition factorizes a matrix into U, Σ, and Vᵀ.

• Orthogonal matrices
• Eigenvalues and eigenvectors

• U = orthogonal matrix (left singular vectors)
• V = orthogonal matrix (right singular vectors)
• \Sigma = diagonal matrix with nonnegative numbers