[Theory] 2/25 Talks at TTIC: Kuikui Liu, University of Washington

Mary Marre mmarre at ttic.edu
Fri Feb 18 19:09:54 CST 2022


*When:*        Friday, February 25th at* 11:30 am CT*


*Where:*       Zoom Virtual Talk (*register in advance here
<https://uchicagogroup.zoom.us/webinar/register/WN_plBFlRGyR9GEghGRimu_Ug>*)


*Who: *         Kuikui Liu, University of Washington


*Title:*          Spectral Independence: A New Tool to Analyze Markov Chains

*Abstract: *Sampling from high-dimensional probability distributions is a
fundamental and challenging problem encountered throughout science and
engineering. One of the most popular approaches to tackle such problems is
the Markov chain Monte Carlo (MCMC) paradigm. While MCMC algorithms are
often simple to implement and widely used in practice, analyzing the
fidelity of the generated samples remains a difficult problem.

In this talk, I will describe a new technique called "spectral
independence" that my collaborators and I developed over the last couple of
years to analyze Markov chains. This technique has allowed us to break
long-standing barriers and resolve several decades-old open problems in
MCMC theory. Our work has opened up numerous connections with other areas
of computer science, mathematics, and statistical physics, leading to
dozens of new developments as well as exciting new directions of inquiry. I
will then discuss how these connections have allowed us to "unify" nearly
all major algorithmic paradigms for approximate counting and sampling.
Finally, I will conclude with a wide variety of future directions and open
problems at the frontier of this research.

*Bio:* Kuikui Liu is a fourth-year PhD student at UW CSE advised by Shayan
Oveis Gharan. He completed his undergraduate studies also at the University
of Washington in 2017, double majoring in computer science and mathematics.
His primary area of expertise is in developing and analyzing algorithms for
sampling from high-dimensional probability distributions encountered
throughout science and engineering. More broadly, he is interested in
algorithmic statistics and the theory of computing. His work has been
recognized by a STOC Best Paper Award.

*Host: **Madhur Tulsiani* <madhurt at ttic.edu>



Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue*
*Chicago, IL  60637*
*mmarre at ttic.edu <mmarre at ttic.edu>*
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