Welcome to Combinatorics and Optimization

Title: Euclidean and projective rigidity of hypergraphs

Abstract: The mathematical theory of structural rigidity has a long history. In the nineteenth century, Cauchy studied rigidity of polyhedra, and Maxwell studied graph frameworks. The rigidity theory of graph frameworks has since been studied extensively. Pollaczek-Geiringer, and later Laman, proved a combinatorial characterization of the minimally rigid graphs in the plane.

Combinatorial rigidity theory is also concerned with geometric realizations of other combinatorial structures. In this talk, we will focus on rigidity of realizations of hypergraphs as points and straight lines. We will discuss how to determine whether a realization of a hypergraph is rigid, in the sense that there are no motions of the realization that preserve the incidences of points and lines, and the distance between any pair of points that lie on a line.

We will also discuss motions of realizations of hypergraphs that preserve only the incidences between points and lines. We will see that classical theorems in incidence geometry, such as Pascal's theorem, make determining rigidity with respect to such motions a difficult problem.

The talk will be based on joint work with K.Stokes and L-D. Öhman, as well as work in progress, joint with L.Berman, B.Schulze, B.Servatius, H.Servatius, K.Stokes and W.Whiteley.

Title: Asymptotic count of edge-bicolored graphs

 Abstract: I will talk about recent joint work with Chiara Meroni and Max Wiesmann, where we showed that specific exponential bivariate integrals serve as generating functions of labeled edge-bicolored graphs. Based on this, we prove an asymptotic formula for the number of regular edge-bicolored graphs with arbitrary weights assigned to different vertex structures.

The asymptotic behavior is governed by the critical points of a polynomial. An interesting application of this purely combinatorial work to mathematical physics is the Ising model on a random graph. I will explain how its phase transitions arise from our formula.

There will be a pre-seminar presenting relevant background at the beginning graduate level starting at 1pm,

Title:The Inexact Augmented Lagrangian Method: Optimal Complexity Bounds and Applications to Solving Huge SDPs

Abstract:In the first part of this talk, we present optimal and nearly-optimal parameter-free augmented Lagrangian (AL) methods for convex and strongly optimization with linear constraints. Our AL methods employ tractable inexact criteria for solving their inner subproblems, which accelerated methods can be shown to achieve in a finite number of iterations that depends on the target accuracy.

In the second part of this talk, we present a new inexact augmented Lagrangian method, namely, HALLaR, that employs a Burer-Monteiro style low-rank factorization for solving large-scale semidefinite programs (SDPs). The AL subproblems are solved by a hybrid low-rank method, which is based on a combination of a low-rank Frank-Wolfe method and a nonconvex accelerated inexact proximal point method. In contrast to the classical low-rank method by Burer and Monteiro, HALLaR finds a near-optimal solution (with provable complexity bounds) of SDP instances satisfying strong duality. Computational results comparing HALLaR to state-of-the-art solvers on several large SDP instances show that the former finds higher accurate solutions in substantially less CPU time than the latter ones. For example, in less than 20 minutes, HALLaR can solve (on a personal laptop) a maximum stable set SDP with 1 million vertices and 10 million edges within 1e-5 relative accuracy.

This talk is based on joint work with Saeed Ghadimi and Henry Wolkowicz from University of Waterloo and Diego Cifuentes and Renato Monteiro from Georgia Tech.