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abstract:
Motivated by an application in computational biology, we consider low-rank matrix
factorization with {0, 1}-constraints on one of the factors and optionally convex
constraints on the second one. In the line of recent work on non-negative matrix factorization by Arora et
al. (2012), we provide an algorithm that provably recovers the underlying factorization in the
exact case. Moreover, we provide conditions under which this factorization is unique. |
