Abstract
The injective norm of a k-tensor is a notoriously difficult quantity to approximate. For example, given a random 4-tensors, spectral techniques yield the best known sqrt{n}-approximation to the injective norm. In this talk, I will describe how n^{\epsilon}-degree SoS SDP hierarchy can be used to improve this approximation to a n^{1/2 -\delta} for some \delta.