DATE:

Friday, October 21, 2022

TIME:

3:30 PM

LOCATION:

GMCS 314

SPEAKER:

Dr. Duy Nguyen, Electrical and Computer Engineering, San Diego State University

ABSTRACT:

A central task in statistical inference is the evaluation of the posterior distribution p(x|y) of the latent variables x given the observed data variables y. For many models of practical interest, it will be infeasible to evaluate the posterior distribution, because the dimensionality of the latent space is too high to work with directly or because the posterior distribution has a highly complex form. In these situations, we need to resort to approximate schemes. In this talk, I will review a range of deterministic approximation schemes, including approximate message passing (AMP) and variational Bayes (VB) inference, which scale well to large applications. These are based on analytical approximations to the posterior distribution, for example by assuming that it factorizes in a particular way. I will present the theory behind AMP and VB and some related computationally efficient algorithms in these schemes. Finally, I will present the applications of approximate inference in (sparse) linear regression,logistic regression, probit regression, compressed sensing, and MIMO signal estimation.

Bio: Duy H. N. Nguyen(Senior Member, IEEE) is an Associate Professor in the Department of Electrical and Computer Engineering, San Diego State University. He received the B.Eng. from Swinburne University of Technology, Hawthorn, VIC, Australia in 2005, the M.Sc.from University of Saskatchewan, Saskatoon, SK, Canada in 2009 and the Ph.D.from McGill University, Montreal, QC, Canada in 2013. He was a postdoctoral research fellow at INRS-EMT (University of Quebec), The University of Houston,and the University of Texas at Austin. He joined SDSU in 2016. His current research interests include resource allocation in wireless networks, signal processing for communications, optimization, game theory and machine learning. He recently received the 2022 NSF CAREER award.

HOST:

Sunil Kumar

VIDEO: