Speaker: Benoit Liquet-Weiland
Affiliation: Macquarie University

Abstract

It is well established that incorporation of prior knowledge on the structure existing in the data for potential grouping of the covariates is key to more accurate prediction and improved interpretability.

In this talk, I will present new multivariate methods incorporating grouping structure in frequentist and Bayesian methodology for variable selection and dimension reduction to tackle the analysis of high dimensional and Big-Data set.  We develop methods using both penalised likelihood methods and Bayesian spike and slab priors to induce structured sparsity. Illustration on genomics dataset will be presented .

About Maths Colloquium

The Mathematics Colloquium is directed at students and academics working in the fields of pure and applied mathematics, and statistics. 

We aim to present expository lectures that appeal to our wide audience.

Information for speakers

Information for speakers

Maths colloquia are usually held on Mondays, from 2pm to 3pm, in various locations at St Lucia.

Presentations are 50 minutes, plus five minutes for questions and discussion.

Available facilities include:

  • computer 
  • data projector
  • chalkboard or whiteboard

To avoid technical difficulties on the day, please contact us in advance of your presentation to discuss your requirements.

Venue

Priestley Building (67)
Room: 
442 (or via Zoom address https://uqz.zoom.us/j/81688396546)