The INI has a new website!

This is a legacy webpage. Please visit the new site to ensure you are seeing up to date information.

Skip to content



The Dantzig selector for high dimensional statistical problems

Rivoirard, V (Paris-Dauphine)

Tuesday 22 March 2011, 16:00-17:00

Seminar Room 1, Newton Institute


The Dantzig selector has been introduced by Emmanuel Candes and Terence Tao in an outstanding paper that deals with prediction and variable selection in the setting of the curse of dimensionality extensively considered in statistics recently. Using sparsity assumptions, variable selection performed by the Dantzig selector can improve estimation accuracy by effectively identifying the subset of important predictors, and then enhance model interpretability allowed by parsimonious representations. The goal of this talk is to present the main ideas of the paper by Candes and Tao and the remarkable results they obtained. We also wish to emphasize some of the extensions proposed in different settings and in particular for density estimation considered in the dictionary approach. Finally, connections between the Dantzig selector and the popular lasso procedure will be also highlighted.


Your browser canít play this video. You do not appear to have a flash player installed.
Please download flash player or choose an alternative format instead.

Get Adobe Flash player

Available Video Formats

Back to top ∧