no code implementations • 4 Sep 2019 • Bernardo B. Gatto, Eulanda M. dos Santos, Alessandro L. Koerich, Kazuhiro Fukui, Waldir S. S. Junior
In this paper, we present a new method for multi-dimensional data classification that relies on two premises: 1) multi-dimensional data are usually represented by tensors, since this brings benefits from multilinear algebra and established tensor factorization methods; and 2) multilinear data can be described by a subspace of a vector space.