Sparse and Low-Rank Tensor Decomposition

An efficient computational algorithm is presented that modifies Leurgans' algorithm for tensor factorization via the notion of tensor contraction and uses well-understood convex techniques for solving the reduced matrix sub-problem which then allows the full decomposition of the tensor.