SMS scnews item created by Linh Nghiem at Fri 22 Apr 2022 1604
Type: Seminar
Distribution: World
Expiry: 28 May 2022
Calendar1: 29 Apr 2022 1400-1500
CalLoc1: AGR Carslaw 829
CalTitle1: Variable Selection and Dimension Reduction methods for high dimensional and Big-Data Set
Auth: linhn@linhs-mbp.staff.wireless.sydney.edu.au (hngh7483) in SMS-SAML

# Statistics Seminar: Liquet-Weiland -- Variable Selection and Dimension Reduction methods for high dimensional and Big-Data Set

Variable Selection and Dimension Reduction methods for high dimensional and Big-Data Set

Time: 14:00 - 15:00 29 April 2022
Location: AGR 829, or Zoom at https://uni-sydney.zoom.us/j/84980973940

Speaker: Prof.  Benoit Liquet-Weiland (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.


Actions:
Calendar (ICS file) download, for import into your favourite calendar application
UNCLUTTER for printing
AUTHENTICATE to mark the scnews item as read
School members may try to .