Ohad Giladi

A Remark on the Convergence of the Douglas–Rachford Iteration in a Non-convex Setting

Using a known construction of a Lyapunov function, it is shown that the Douglas–Rachford iteration with respect to a sphere and a line in a Hilbert space converges to the intersection point in a fashion which is stronger than uniform convergence on compact sets.

Small Ball Estimates for Quasi-Norms

This note contains two types of small ball estimates for random vectors in finite-dimensional spaces equipped with a quasi-norm. In the first part, we obtain bounds for the small ball probability of random vectors under some smoothness assumptions on their density function. In the second part, we obtain Littlewood–Offord type estimates for quasi-norms. This generalizes results which were previously obtained in Friedland and Sodin (C R Math Acad Sci Paris 345(9):513–518, 2007), and Rudelson and Vershynin (Commun Pure Appl Math 62(12):1707–1739, 2009).

A Perron–Frobenius type result for integer maps and applications

It is shown that for certain maps, including concave maps, on the d-dimensional lattice of positive integer points, ‘approximate’ eigenvectors can be found. Applications in epidemiology as well as distributed resource allocation are discussed as examples.

A Lyapunov Function Construction for a Non-convex Douglas–Rachford Iteration

While global convergence of the Douglas–Rachford iteration is often observed in applications, proving it is still limited to convex and a handful of other special cases. Lyapunov functions for difference inclusions provide not only global or local convergence certificates, but also imply robust stability, which means that the convergence is still guaranteed in the presence of persistent disturbances. In this work, a global Lyapunov function is constructed by combining known local Lyapunov functions for simpler, local subproblems via an explicit formula that depends on the problem parameters. Specifically, we consider the scenario, where one set consists of the union of two lines and the other set is a line, so that the two sets intersect in two distinct points. Locally, near each intersection point, the problem reduces to the intersection of just two lines, but globally the geometry is non-convex and the Douglas–Rachford operator multi-valued. Our approach is intended to be prototypical for addressing the convergence analysis of the Douglas–Rachford iteration in more complex geometries that can be approximated by polygonal sets through the combination of local, simple Lyapunov functions.

Inverse Littlewood---Offord Problems for Quasi-norms

Given a compact star-shaped domain

Some Remarks on Convex analysis in topological groups

K\subseteq \mathbb {R}^d

On the geometry of projective tensor products

K⊆Rd, n vectors