UBC Mathematics of Information Colloquium: Sinho Chewi

  • Date: 02/03/2023
Sinho Chewi, MIT

University of British Columbia


Towards a theory of complexity of sampling, inspired by optimization


Sampling is a fundamental and widespread algorithmic primitive that lies at the heart of Bayesian inference and scientific computing, among other disciplines. Recent years have seen a flood of works aimed at laying down the theoretical underpinnings of sampling, in analogy to the fruitful and widely used theory of convex optimization. In this talk, I will discuss some of my work in this area, focusing on new convergence guarantees obtained via a proximal algorithm for sampling, as well as a new framework for studying the complexity of non-log-concave sampling.

Other Information: 

A reception will be held before the Colloquium: Tea/coffee and light snacks

Date/time: Friday, February 3rd, 2:15pm

Location: PIMS lounge ESB 4133

Lecture time: 3:00pm Pacific. ESB 2012