Parallel algorithms for tensor completion in the CP format
Novel parallel algorithms for tensor completion problems, with applications to recommender systems and function learning. Parallelization strategy offers greatly reduced memory requirements compared to previously published matrix equivalents. Convergence results for both alternating least squares and cyclic coordinate descent.
low-rank tensor completion canonical tensor format parallel tensor completion parallel cyclic coordinate descent parallel alternating least squares