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Parallel Nonnegative CP Decomposition of Dense Tensors
[article]
2018
arXiv
pre-print
The CP tensor decomposition is a low-rank approximation of a tensor. We present a distributed-memory parallel algorithm and implementation of an alternating optimization method for computing a CP decomposition of dense tensor data that can enforce nonnegativity of the computed low-rank factors. The principal task is to parallelize the matricized-tensor times Khatri-Rao product (MTTKRP) bottleneck subcomputation. The algorithm is computation efficient, using dimension trees to avoid redundant
arXiv:1806.07985v1
fatcat:qx6g7qsrxvfsll2hu464cdvqsi