Events

Rota's Conjecture

Abstract:

In 1970, Gian-Carlo Rota posed a conjecture giving a succinct
combinatorial characterization of the linear dependencies among a finite set of vectors in a vector space over any given finite field.

A Proof of the Manickam-Mikl\'{o}s-Singhi Conjecture for Vector Spaces

Abstract:

Let $V$ be an $n$-dimensional vector space over a finite field.
Assign a real-valued weight to each $1$-dimensional subspace in $V$ so

The Boundary Structure of Spectrahedra Arising from the Lovász Theta Function

Abstract:

The theta body TH(G) of a graph G is a semidefinite relaxation of
STAB(G), the stable set polytope of G, and it is contained in QSTAB(G),

Stable Polynomials and Ramanujan Graphs

Abstract:

We show how Marcus, Spielman and Srivastava use stable polynomials to construct bipartite Ramunujan graphs of degree $k$ whenever $k\ge3$. (This will be the second of two lectures.)

Faster private release of marginals on small databases

Abstract:

The goal of privacy-preserving data analysis is to enable rich statistical analyses on the database while protecting the privacy of the individual records.

Problems in Algebraic Graph Theory

Abstract:

Problems in algebraic graph theory will be discussed.

Solution geometry of a random k-XORSAT near the clustering threshold

Abstract:

Since early 2000s statistical physicists predicted, using a non-rigorous
technique called the "cavity method", that the solution spaces of many

Finding small stabilizers for unstable graphs

Abstract:

A vertex v of a graph G is called inessential if there exists a maximum matching in G that exposes v. G is said to be stable if the set of its inessential vertices forms a stable set.

Recent Results on Tensor and Polynomial Optimization

Abstract

Tensor/polynomial optimization is a relatively new and active area of research in optimization. In this talk we shall present some new results on the computational models in tensor and polynomial optimization.

Sparsity and gauge optimization

Abstract:

Gauge functions significantly generalize the notion of a norm, and gauge optimization is the class of problems for finding the element of a convex set that is minimal with respect to a gauge.