| # Low-rank approximation of a matrix via its SVD Returning to this example, involving a matrix with row size and column size : As seen here, the SVD is given by , with The matrix is rank . A rank-two approximation is given by zeroing out the smallest singular value, which produces We check that the Frobenius norm of the error is the sum of singular values we have zeroed out, which here reduces to :