Robert Tibshirani  The Lasso and interaction models
Vortrag Robert Tibshirani (USA) über "The Lasso and interaction models"
Was 


Wann 
11.07.2012 von 11:15 bis 12:15 
Wo  Hörsaal Virologie, HermannHerderStraße 11 
Name  AnneSophie Stöhlker 
Termin übernehmen 
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Special date: Wednesday!
Raumänderung: Hörsaal Virologie, HermannHerderStraße 11
Robert Tibshirani Professor of Statistics and Health Research and Policy
Stanford University School of Medicine, California (USA)
The Lasso is a popular tool for highdimensional model building. First I will review recent computational advances that enable the Lasso to be applied to large datasets. Then I will describe very recent work on fitting interaction models. Statisticians commonly demand that an interaction only be included in a model if both variables are marginally important. We study the problem of identifying hierarchical twoway interaction models from the viewpoint of the Lasso (i.e., L1penalized regression). We show that by adding a set of convex constraints to the Lasso problem, we can produce sparse interaction models that honor the hierarchy restriction. In contrast to stepwise procedures that are most commonly used for building interaction models, our formulation is convex, and its solution is completely characterized by a set of optimality conditions. This makes it easier to study as a statistical estimator. We argue that restricting to hierarchical interactions can be advantageous both statistically and computationally. We study its properties, give examples and present an efficient computational algorithm.
This is based on the PhD thesis work of my student Jacob Bien and is also joint with Jonathan Taylor.