[Lisa_seminaires] Kevin Murphy @ McGill on Friday

Dumitru Erhan dumitru.erhan at umontreal.ca
Mer 25 Mar 12:54:07 EDT 2009


To make things clearer:

The talk is this coming Friday (March 27th) at 11am. The location is
Macdonald-Harrington G-01, which is at McGill university.

Sorry for the confusion,
Dumitru

On Tue, Mar 24, 2009 at 16:33, Dumitru Erhan <dumitru.erhan at umontreal.ca> wrote:
> Title: Computationally and statistically efficient methods for model
> selection in graphical models
>
> Speaker: Kevin Murphy (Stats/CS, U. British Columbia)
>
> Time/Place: Friday, 11am in Macdonald-Harrington G-01
>
> Abstract:
>
> Graphical models are a way of representing conditional independence
> relationships between random variables using graphs. In this talk, we
> discuss ways of learning the structure of graphs from data. This is
> useful for visualizing relationships between variables in
> high-dimensional data, as well as for building density models for use in
> prediction, classification, clustering, etc. We will focus on undirected
> graphs (also called random fields), and in particular on methods based
> on L1-penalized maximum likelihood. First we extend existing results for
> the Gaussian and binary case to the more general case of conditional
> random fields and multi-state models. This requires that we replace the
> L1 penalty with a group L1 penalty, which poses various computational
> challenges. The second extension is to estimate the group structure (by
> clustering the variables) while simultaneously learning the graph
> structure. This technique relies on new bounds on the partition function
> for the positive definite matrix Laplace distribution, which also has
> applications in hierarchical Bayesian analysis of multiple related graphs.
>



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