Predicting Directed Links Using Nondiagonal Matrix Decompositions

We present a method for trust prediction based on no diagonal decompositions of the asymmetric adjacency matrix of a directed network. The method we propose is based on a no diagonal decomposition into directed components (DEDICOM), which we use to learn the coefficients of a matrix polynomial of the network's adjacency matrix. We show that our method can be used to compute better low-rank approximations to a polynomial of a network's adjacency matrix than using the singular value decomposition, and that a higher precision can be achieved at the task of predicting directed links than by undirected or bipartite methods.