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GERAD seminar

Restricted lasso and double shrinking


Mar 3, 2017   10:45 AM — 12:00 PM

Mina Norouzirad Shahrood University of Technology, Iran

In last decade, the lasso (least absolute shrinkage and selection operator) estimator is one of the most famous shrinkage and selection techniques in the multiple linear regression. Sometimes some prior knowledge like linear constraints on some important factors is at hand. Therefore, one may restrict the lasso estimator to combine this information within the lasso estimator. Since the lasso shrinks the coefficients already, a double shrinkage estimator is born.

Free entrance.
Welcome to everyone!

Vahid Partovi Nia organizer


Room 4488
André-Aisenstadt Building
Université de Montréal Campus
2920, chemin de la Tour
Montréal QC H3T 1J4