Polynomial optimization encompasses a very rich class of problems in which both the objective and constraints can be written in terms of polynomials on the decision variables. There is a well established body of research on quadratic polynomial optimization problems based on reformulations of the original problem as a conic program over the cone of completely positive matrices, or its conic dua...

We study the left-invertibility of infinite matrices indexed by metric spaces with polynomial growth. Under different conditions on the rows and the columns, we prove that being bounded-below in lp for some 1 ≤ p ≤ ∞, implies that there is a left-inverse which is bounded in lq, for all 1 ≤ q ≤ ∞. In particular, this applies to matrices with polynomial decay, indexed by discrete groups of polyno...

We study the problem of dictionary learning for signals that can be represented as polynomials or polynomial matrices, such as convolutive signals with time delays or acoustic impulse responses. Recently, we developed a method for polynomial dictionary learning based on the fact that a polynomial matrix can be expressed as a polynomial with matrix coefficients, where the coefficient of the poly...

We investigate the use of polynomial matrices to give efficient presentations of nonnegative matrices exhibiting prescribed spectral and algebraic behavior.