Then, Once the matrix X is obtained, we perform its singular value decomposition (SVD) and approximate it by keeping the largest R singular values and setting the rest to zero.
where, U(IJ × R) and V(K × R) are orthonormal matrices and S(R×R) is a diagonal matrix.