Hello everyone,
Today we will have a Statistics and Data Science seminar.
Our speaker is Vitaly Zankin, The Alan Turing Institute and the details of the talk are listed below.
The seminar is scheduled for 4:30pm and it will be online. You can join via Zoom using the link
https://tennessee.zoom.us/j/93493296803
Best,
Ioannis
Title: Sparse Online Variational Bayesian Inference
Abstract: This work aims to study variational Bayesian inference for sparse regression. Sparsity promoting priors have proven to be very successful in regression scenarios since it helps to select meaningful features and avoid overfitting (e.g. LASSO regression or total variation (TV) regularization in imaging). We focus on a general class of shrinkage priors that can be represented as a scale mixture of normal distributions with a generalized inverse Gaussian distribution and includes such priors as Laplace, Generalized Jeffrey's, Student-t and others. However, since shrinkage priors are non-Gaussian, a fully Bayesian solution becomes very expensive, requiring MCMC methods. To alleviate this, we employ a variational approach that leverages a generalization of the expectation-maximization algorithm to recover the best Gaussian approximation to the sparsity-promoting posterior. This approach turns out to be especially fast and scalable in the case of linear models, where it provides approximate UQ for a substantially smaller cost than fully Bayesian approaches yet keeping comparable accuracy. Besides, the proposed approach supports online inference to process the data in batches and strategies for online hyperparameter estimation. The high performance in terms of the variable selection and UQ is demonstrated for complex real and simulated data examples where it competes against MCMC based methods as well as the other approximate approaches.
—
Ioannis Sgouralis, Ph.D.
Assistant Professor
Department of Mathematics
University of Tennessee, Knoxville
e-mail: [log in to unmask]
web: https://www.math.utk.edu/info/labs/sgouralis
zoom: tennessee.zoom.us/my/sgouralis
twitter: @SgouralResearch
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