[Lisa_seminaires] Fwd: J'organise ce séminaire au GERAD, mercredi 7 déc., 15h45

Yoshua Bengio yoshua.umontreal at gmail.com
Lun 5 Déc 09:29:12 EST 2016


---------- Message transféré ----------
De : *Pierre Lecuyer* <lecuyer at iro.umontreal.ca>
Date : lundi 5 décembre 2016
Objet : J'organise ce séminaire au GERAD, mercredi 7 déc., 15h45
À : seminaires <seminaires at iro.umontreal.ca>, "Manuel Morales (UdeM)" <
morales at dms.umontreal.ca>, Christian Leger <leger at dms.umontreal.ca>,
francois.bellavance at hec.ca, cgenest at math.mcgill.ca, MACGIBBON BRENDA <
macgibbon.brenda at uqam.ca>, bruno.remillard at hec.ca, Francois Perron <
perronf at crm.umontreal.ca>, bedard at dms.umontreal.ca, hatem ben-ameur <
hatem.ben-ameur at hec.ca>, cotemyri at iro.umontreal.ca, Zdravko Botev <
botev at unsw.edu.au>


SVP diffuser aux intéressés.

Détails ici:  https://www.gerad.ca/fr/events/1407


Novel computational approaches to the Bayesian and frequentist lasso
regression Zdravko I. Botev <http://web.maths.unsw.edu.au/%7Ezdravkobotev/> –
The University of New South Wales, Australie

The Lasso regression model is one of the simplest and most popular
penalized regression models in statistics. In this talk we describe a
simple Monte Carlo method for sampling from the posterior density of the
Bayesian posterior of the Lasso. We show how the construction of such an
efficient Monte Carlo sampler necessitates that we solve the frequentist
Lasso optimization problem in a novel way. We give a numerical example with
the well-known diabetes dataset of Efron.

This is joint work with Pierre L'Ecuyer.
------------------------------

-- 
Pierre L'Ecuyer, Professeur Titulaire
Chaire du Canada en Simulation et Optimisation Stochastique
CIRRELT, GERAD, and DIRO, Université de Montréal,
Canadahttp://www.iro.umontreal.ca/~lecuyer
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