  We present a novel game-theoretic formulation of Non-Negative Matrix
Factorization (NNMF), a popular data-analysis method with many scientific and
engineering applications. The game-theoretic formulation is shown to have
favorable scaling and parallelization properties, while retaining
reconstruction and convergence performance comparable to the traditional
Multiplicative Updates algorithm.
