We are going to discuss Ramon van Handel's new tutorial on Structured Random Matrices.
It reviews a number of recent results and methods related to the study of non i.i.d. random matrices, when the goal is to understand how the given structure of the matrix (like sparsity, dependent entries etc) is reflected in its spectral properties. This week we will talk about non commutative Khinchine inequality, that bounds the moments of a random matrix (which immediately results in a bound of its spectral norm). Often this bound is only log-optimal, but it has a power of being remarkably general: it does not even require independence of the matrix entries. Speaker(s): Liza Rebrova (UM)