  In this paper, we propose a simple algorithm to cluster nonnegative data
lying in disjoint subspaces. We analyze its performance in relation to a
certain measure of correlation between said subspaces. We use our clustering
algorithm to develop a matrix completion algorithm which can outperform
standard matrix completion algorithms on data matrices satisfying certain
natural conditions.
