Ihaka Lecture Series | Four | Statistical learning and sparsity Event as iCalendar

03 April 2019

6:30pm

Venue: Lecture Theatre PLT1, Ground Floor, Building 303, 38 Princes Street, City Campus

Location: Please join us for refreshments from 6pm outside the lecture theatre

Host: Department of Statistics

Cost: Free - all welcome

Professor Robert Tibshirani, Stanford University Ihaka Lecture Series 2019 speaker
Professor Robert Tibshirani

In this talk Professor Robert Tibshirani will review the lasso method for high dimensional supervised learning and discuss some new developments in the area, including the Pliable Lasso, and post-selection inference for understanding the important features.

Professor Tibshirani will also describe some applications of these methods to his own collaborative work, including prediction of platelet usage at Stanford Hospital.

Watch the lecture.
 

About the speaker

Rob Tibshirani is Professor of Statistics and Biomedical Data Science at Stanford University. His main interests are in applied statistics, biostatistics and data science. He is most well-known for the LASSO, which is a shrinkage and selection method for linear regression.

He is the co-author of the books Generalized Additive Models (with T. Hastie), An Introduction to the Bootstrap (with B. Efron), An Introduction to Statistical Learning (with G. James, D. Witten and T. Hastie), Sparsity in Statistics (with T. Hastie and M. Wainwright), and the widely used Elements of Statistical Learning (with T. Hastie and J. Friedman).

His current research focuses on problems in biology and genomics, medicine, and industry.

Read more about the Ihaka Lecture Series.

The New Zealand Statistical Association

Our thanks to The New Zealand Statistical Association who are our official sponsors for the 2019 Ihaka Lecture Series.