By repeating the above procedures for all large eigen­values, a good spectral graph sparsifier can be obtained.
computing the largest eigenvalue and its eigenvector can be too costly for large-scale graph Laplacian matrices, even when state-of-the-art eigenvalue decomposition methods are considered [18].