[Forum SIS] seminar: Chris Holmes

[Irene Poli]

 European Centre for Living Technology (ECLT) ,  University Ca' Foscari Venice  (www.ecltech.org)

 Seminar announcement 



          Monday 23rd May at 11.00 am,  in the Conference Room of Ca' Minich 


                                                                                         

Prof. Chris Holmes                                              

University of Oxford, UK

Bayesian nonparametric mixture modelling of sparse signals with cluster specific variable selection

                                            

Abstract:   

We discuss a hierarchical Bayesian nonparametric mixture model for clustering when some of the covariates are assumed to be of varying relevance to the clustering problem. This can be thought of as an issue in variable selection for unsupervised learning. We demonstrate that by defining a hierarchical population based nonparametric prior on the cluster locations scaled by the inverse covariance matrices of the likelihood we arrive at a ‘sparsity prior’ representation which admits a conditionally conjugate prior. This allows us to perform full Gibbs sampling to obtain posterior distributions over parameters of interest including an explicit measure of each covariate’s relevance and a distribution over the number of potential clusters present in the data. This also allows for individual cluster specific variable selection. We demonstrate improved inference on a number of canonical problems including analysis of patterns of copy-number-variation present in colon cancer genomes.

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Seminars at ECLT are jointly organised by Irene Poli and Phil Brown.
Further information on the seminars is available at www.ecltech.org


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