Statistical Methods for the analysis of high dimensional data
University of Melbourne
by Hugh Miller
Abstract: High-dimensional problems, where there are many more variables than observations, have captured the imagination of statisticians worldwide, due to the variety of applications and the theoretical challenges involved. This talk will cover the topics of my PhD research,
* How to reduce dimensionality to a manageable level, even when strong variable correlations and nonlinearities are present
* How to assess the variability of a ranking of the dimensions, and how reliable they are under a variety of circumstances
* How to build predictive models while protecting against overfitting The talk will aim to be fairly accessible, and will cover both theoretic settings and real data applications.
For More Information: For more information please contact Hugh Miller: firstname.lastname@example.org