QLunch: On tensors of minimal border rank
Speaker: Vladimir Lysikov from QMATH
Title: On tensors on minimal border rank
Abstract: Rank of a tensor is a natural measure of its complexity which generalizes usual notion of matrix rank to higher order tensors. Unlike in the matrix case, the set of all tensors of bounded rank is not closed, making it possible for a tensor of high rank to be approximated arbitrarily closely by tensors of lower rank. We explore the connection between these tensor approximations and deformations of commutative algebras.