We provide an overview of our main results about studying Linear Programming Problems whose coefficient matrix is subject to uncertainty and the uncertainty is modeled through a multi-band set. Such an uncertainty set generalizes the classical one proposed by Bertsimas and Sim [3] and is particularly suitable in the common case of arbitrary non-symmetric distributions of the parameters. Our inv...

We propose different formulations as well as efficient solution approaches for the VPN design problem under traffic uncertainty with symmetric bandwidths.

We extend the classical Uncertainty Principle to the context of Gelfand pairs. The Gelfand pair setting includes riemannian symmetric spaces, compact topological groups, and locally compact abelian groups. If the locally compact abelian group is Rn we recover a sharp form of the classical Heisenberg uncertainty principle. Section

in this paper we introduce two symmetric variants of amenability, symmetric module amenability and symmetric connes amenability. we determine symmetric module amenability and symmetric connes amenability of some concrete banach algebras. indeed, it is shown that $ell^1(s)$ is  a symmetric $ell^1(e)$-module amenable if and only if $s$ is amenable, where $s$ is an inverse semigroup with subsemigr...

We prove two versions of Beurling’s theorem for Riemannian symmetric spaces of arbitrary rank. One of them uses the group Fourier transform and the other uses the Helgason Fourier transform. This is the master theorem in the quantitative uncertainty principle.

We provide an overview of the main results that we obtained studying uncertain mixed integer linear programs when the uncertainty is represented through the new multiband model [4]. Such model extends and refines the classical one proposed by Bertsimas and Sim [2] and is particularly suitable in the common case of arbitrary non-symmetric distributions of the uncertainty. Our investigations were...