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Please notice: after  April 30, 2010,  a late registration fee applies



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              *           ABS10             *
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             Applied Bayesian Statistics School

BAYESIAN MACHINE LEARNING WITH BIOMEDICAL APPLICATIONS

   June, 11 - 15, 2010 - Bolzano/Bozen, Italy


Lecturer

Prof. David B. Dunson
Department of Statistical Science, Duke University
Durham, NC, USA

Programme and registration details are available at

>>>>   www.mi.imati.cnr.it/conferences/abs10.html   <<<<

Interested people are invited to contact the ABS10 Secretariat at

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---------------- COURSE OUTLINE ---------------------------------------

This short course is intended to provide a practically-motivated
introduction to Bayesian methods for machine learning and
high-dimensional data analysis. Some topics of particular interest
include high-dimensional variable selection for regression and
classification, and multi-task learning and combining of information
for related signals, functions or images. A brief overview will be
provided of Bayesian methods for linear regression with very many
predictors using shrinkage priors and mixture priors. This overview
will include Bayesian formulations of Lasso, elastic net and relevance
vector machine (RVM) methods that have been widely used in the
literature. In addition, spike and slab mixture priors for formal
Bayes subset selection and model averaging will be presented. We also
describe sparse Bayesian latent factor regression methods, which can
accommodate selection of correlated sets of predictors in large p,
small n settings. Computational methods will be described based on
maximum a posteriori estimation and Markov chain Monte Carlo
algorithms. The methods will be compared through simulation studies
and applied to a variety of data examples, including machine learning
data and biomedical applications involving gene expression and other
high-dimensional markers. An emphasis will be on practical issues in
implementing and interpreting results, and code will be provided in R
and Matlab.

The school will make use of lectures, practical sessions, software
demonstrations, informal discussion sessions and presentations of
research projects by school participants. The slides and background
reading material will be distributed to the students before the start
of the course.
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Guido Consonni and Fabrizio Ruggeri
ABS10 Directors

-- 
Fabrizio Ruggeri                    fabrizio AT mi.imati.cnr.it
CNR IMATI                           tel +39 0223699532
Via Bassini 15                      fax +39 0223699538
I-20133 Milano (Italy)              www.mi.imati.cnr.it/~fabrizio

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