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CNR: Alamanacco della Scienza


N. 4 - 28 apr 2010
ISSN 2037-4801

International info   a cura di Cecilia Migali


Bayesian machine learning with biomedical applications

Jointly organized by Imati-Cnr of Milano and University of Pavia, in cooperation with the European academy Bozen/Bolzano (Eurac), through the Institute of genetic medicine, the applied Bayesian statistics school 2010 will take place in Bolzano, Italy, June 11 through 15, 2010.

It aims to present state-of-the-art Bayesian applications, inviting leading experts in their field. Each year a different topic is chosen. The topic chosen for the 2010 school is Bayesian machine learning with biomedical applications. The lecturer is Prof. David Dunson, Department of statistical science, Duke University, Durham, NC, Usa

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. 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.


Fonte: Fabrizio Ruggeri, Istituto di matematica applicata e tecnologie informatiche, Milano, tel. 02 23699532, email fabrizio@mi.imati.cnr.it

Per saperne di più: - www.mi.imati.cnr.it