  The Rank Minimization Problem asks to find a matrix of lowest rank inside a
linear variety of the space of n x n matrices. The Low Rank Matrix Completion
problem asks to complete a partially filled matrix such that the resulting
matrix has smallest possible rank.
  The Tensor Rank Problem asks to determine the rank of a tensor. We show that
these three problems are equivalent: each one of the problems can be reduced to
the other two.
