Previous Conferences & Workshops

I'll describe joint work with Sheel Ganatra and Nick Sheridan which rigorously establishes the relationship between different aspects of the mirror symmetry phenomenon for Calabi-Yau manifolds. Homological mirror symmetry---an abstract, categorical...

In this talk, I will discuss our recent efforts to formalize a particular notion of “fairness” in online decision making problems, and study its costs on the achievable learning rate of the algorithm. Our focus for most of the talk will be on the...

A result of Gelfand and Graev shows that the supercuspidal representations of $\mathrm{SL}_2$ are neatly parameterized by characters of elliptic tori, and that the stable character data for all such representations may be collected into a single...

We'll take a glance at the world of mathematics as viewed through the Univalent Foundations of Voevodsky. In it, "set" and "proposition" are defined in terms of something more fundamental: "type". The formal language fulfills the mathematicians'...

In this talk we will quantify the coupling asymptotics for the Lyapunov exponent (LE) of a one-frequency quasi-periodic Schrödinger operator with analytic potential sampling function. By proving an asymptotic formula for the LE valid for all...

We explain how the Edge-reinforced random walk, introduced by Coppersmith and Diaconis in 1986, is related to several models in statistical physics, namely the supersymmetric hyperbolic sigma model studied by Disertori, Spencer and Zirnbauer (2010)...

The sensitivity conjecture is a famous open problem in the theory of boolean functions. Let $f$ be a boolean function defined on the hypercube. The sensitivity of a node $x$ is the number of its neighbours in the hypercube, for which $f$ give the...

The tree amplituhedron $A(n,k,m)$ is the image in the Grassmannian $Gr(k,k+m)$ of the totally nonnegative part of $Gr(k,n)$, under a (map induced by a) linear map which is totally positive. It was introduced by Arkani-Hamed and Trnka in 2013 in...

An active learning algorithm for a classification problem has access to many unlabelled samples. The algorithm asks for the labels of a small number of samples, carefully chosen, such that that it can leverage this information to correctly label...