tensorly.contrib.sparse.decomposition.symmetric_parafac_power_iteration

symmetric_parafac_power_iteration(tensor, rank, n_repeat=10, n_iteration=10, verbose=False)

Symmetric CP Decomposition via Robust Symmetric Tensor Power Iteration

Parameters:	tensortl.tensor input tensor to decompose, must be symmetric of shape (size, )*order rankint rank of the decomposition (number of rank-1 components) n_repeatint, default is 10 number of initializations to be tried n_iterationsint, default is 10 number of power iterations verbosebool level of verbosity
Returns:	(weights, factor) weights1-D tl.tensor of length rank contains the eigenvalue of each eigenvector factor2-D tl.tensor of shape (size, rank) each column corresponds to one eigenvector