Past Events

Stochastic variance reduction techniques have been influential for developing algorithms for minimization problems in the last decade whereas their use in more general problem templates has been limited. This talk will present a first order algorithm...

We investigate a self-interacting random walk, in a dynamically evolving environment, which is a random tree built by the walker itself, as it walks around. At time n=1,2,…n=1,2,…, right before stepping, the walker adds a random number (possibly zero...

A Dirichlet character over Fq(t) corresponds to a curve over Fq. Using this connection to geometry, we construct families of characters whose L-functions vanish (resp. does not vanish) at the central point. The existence of infinitely many vanishing...

In recent years, the problem of optimal transport has received significant attention in statistics and machine learning due to its powerful geometric properties. In this talk, we introduce the optimal transport problem and present concrete...

A famous conjecture of Stanley states that his chromatic symmetric function distinguishes trees. As a quasisymmetric analogue, we conjecture that the chromatic quasisymmetric function of Shareshian and Wachs and of Ellzey distinguishes directed trees...

Permafrost is the ground that remains frozen for two or more years, and is a complex environment with great importance to climate studies. The role of applied and computational mathematics is to identify and close various gaps in these studies which...

Pro-p groups arise naturally in number theory as quotients of absolute Galois groups over number fields. These groups are quite mysterious. During the 60's, Koch gave a presentation of some of these quotients. Furthermore, around the same period...

Gliomas are the most prevalent, aggressive, and invasive subtype of primary brain tumors, characterized by fast cell growth, strong invasion capability, and well-developed tumor vasculature. Their growth and migration in the brain is a highly complex...

What are the optimal algorithms for learning from data? Have we found them already, or are better ones out there to be discovered? Making these questions precise, and answering them, requires taking on the mathematically deep interplay between...