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SUMMARY:Model selection with Lasso-Zero and a robust extension with an app
 lication to the problem of missing covariates - Sylvain Sardy\, Universit
 é de Genève
DTSTART:20190201T160000Z
DTEND:20190201T170000Z
UID:TALK115912@talks.cam.ac.uk
CONTACT:Dr Sergio Bacallado
DESCRIPTION:We propose a new model selection technique based on the limit 
 of the lasso path as the penalty parameter tends to zero. The method prova
 bly  guarantees model selection under a weaker condition than the lasso an
 d performs better empirically in terms of false discovery rate (FDR). We e
 xtend the method to the situation of missing covariates.\n\n
LOCATION:MR12
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