In Hartford et al . ( 2018 ) the authors provide an impressive generalization of the case of node - value data to several node sets , V 1 , V 2 , . . . , V m of sizes n 1 , n 2 , . . . , n m . Their goal is to learn interactions across sets . That is , an input data point is a tensor A ∈ R n1×n2×···×nm that assigns a value to each element in the cartesian product V 1 × V 2 × · · · × V m . Renumbering the nodes in each node set using permutation matrices P 1 , . . . , P m ( resp . ) results in a new tensor we denote by P 1 : m A.