Full Name
Ashia Wilson
Job Title
Assistant Professor
Company
MIT
Speaker Bio
a Lister Brothers Career Development Assistant Professor at MIT. My research focuses on designing scalable, reliable and socially responsible AI systems using tools from dynamical systems theory, statistics, and optimization. Here is a list of some information about me (CV, Publications, Contact). Short Bio: I obtained my B.A. from Harvard with a concentration in applied mathematics and a minor in philosophy, and my Ph.D. from UC Berkeley in statistics. Before joining MIT, I held a postdoctoral position in the machine learning and statistics group at Microsoft Research.
Speaking At
Abstract
This talk views the problem of sampling from distributions supported on a convex body through the lens of classical non-Euclidean optimization methods namely mirror methods and natural gradient methods. These respectively form the basis of two new algorithms for constrained sampling — the Metropolis-Adjusted Mirror-Langevin Algorithm and the Metropolis-Adjusted Preconditioned Langevin Algorithm, which I will present in this talk. This talk will focus on the mixing time guarantees of these algorithms — an essential theoretical property for MCMC methods — under natural conditions over the target distribution and the geometry of the domain.
