A Combinatorial Approach to $L_1$-Matrix Factorization
Recent work on low-rank matrix factorization has focused on the missing data problem and robustness to outliers and therefore the problem has often been studied under the $L_1$-norm. However, due to the non-convexity of the problem, most algorithms are sensitive to initialization and tend to get stuck in a local optimum. In this paper, we present a new theoretical framework aimed at achieving opt