tensorly.contrib.sparse.decomposition.symmetric_parafac_power_iteration
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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