In general terms, a Tauberian theorem deals with the relationship between the properties of one transform of a measure with those of another transform. We will introduce the notion of a Tauberian theorm, and present our own recent theorem in this direction. Our theorem provides a uniform theory for the construction of certain localized kernels […]

In this talk, we'll discuss the problem of constructing meaningful distances between probability distributions given only finite samples from each distribution.  We approach this through the use of data-adaptive and localized kernels, and in a variety of contexts.  First, we construct locally adaptive kernels to define fast pairwise distances between distributions, with applications to unsupervised […]

What do swarm robotics and political redistricting have in common? One answer is Markov chains, which have recently been used in very different ways to address problems in both these areas. To get a large swarm to exhibit a desired behavior, one solution is to make each individual in the swarm fairly intelligent; another is […]

Knotting in living organisms is a feature that is visible to the careful observer of biological life.  Since the 1970’s, with the increasing power of electron microscopes, scientists have been able to capture images of such structures in living organisms at near atomic levels.  We will explore the mathematics of knotting that has provided tools study these […]

Many problems, arising in discrete and metric geometry, signal processing, physics, etc, can be reformulated as questions of optimizing discrete or continuous measures. We shall review some of such conjectures, as well as approaches to determining optimal (or at least good) point distributions and measures, and connections to other problems, such as discrepancy, sphere packings […]