Past Events

Motivated by parallels between mean eld games and random matrix theory, we develop stochastic optimal control problems and viscosity solutions to Hamilton-Jacobi equa- tions in the setting of non-commutative variables. Rather than real vectors, the...

This special session is organized by the PIMS kantorovich Initiative (kantorovich.org) which is dedicated towards research in the mathematics of Monge-Kantorovich optimal transport and its numerous applications to multiple areas of mathematics...

The degeneracy of a graph is a measure of sparseness that gives important information about its Ramsey- and Turán-type properties. I will talk about the hypergraph extension of these problems. The typical notion of hypergraph degeneracy does not give...

The question of which nilpotent Lie algebras admit complex structures is far from being understood. In recent decades, progress has primarily focused on providing algebraic obstructions to the existence of such structures, with classification results...

This session will highlight the research of Indigenous mathematicians and mathematics, showcasing the breadth and depth of their contributions across various mathematical disciplines. From theoretical research to practical applications and...

Gradient flows have emerged as a powerful framework for analyzing machine learning and statistical inference algorithms. Motivated by several applications in statistical inference, generative models, generalization, and robustness of learning...

Current LLM alignment techniques use pairwise human preferences at a sample level, and as such, they do not imply an alignment on the distributional level. We propose in this paper Alignment via Optimal Transport (AOT), a novel method for...

A vibrant and classic area of research is that of relating the size of a set to the finite point configurations that it contains. Here, size may refer to cardinality, dimension, or measure. It is a consequence of the Lebesgue density theorem, for...

Mathematical models of human interactions are important and widely used in epidemiology and many other fields, but building and working with these models at scale is challenging. I will explain two software tools for doing this, both based on...

There has been extensive study of diagonalization of matrices. Diagonalization can be viewed as using a similarity transform to concentrate the magnitude of all entries within as small a subset of entries as possible. We motivate and present results...