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SSA Canberra branch meeting, featuring Dr Clara Grazian

  • 1 Mar 2022 7:46 AM
    Reply # 12631148 on 12614752
    Francis Hui (Administrator)

    Hi everyone, 

    A reminder of the awesome SSA Canberra online talk this evening. If you love mixture models and soft classification, and equally or love Bayes methods even more, then you are going to love this talk!

    Please see <> for details to RSVP for the Zoom link!


    SSA Canberra   

  • 21 Feb 2022 3:34 PM
    Message # 12614752
    Francis Hui (Administrator)

    Dear SSA et al.,

    Please forward to those who may be interested.

    SSA Canberra Branch will be holding its first meeting for 2022 on Tuesday 1st March via Zoom. 

    Zoom link: Details given at the end of this post. Please note RSVP is required.

    Date: Tuesday 1 March 2022

    Time: 5:45pm – 6:45pm AEDT (Zoom link will open at 5.30pm for pre-mingling)   

    Speaker: Dr Clara Grazian, University of NSW, Sydney

    Topic: A loss-based prior distribution on the number of components of mixture models.

    AbstractFrom a Bayesian perspective, mixture models have been characterised by a restrictive prior modelling, since their ill-defined nature makes most of the improper priors not acceptable. In particular, recent results have shown the inconsistency of the posterior distribution on the number of components when using standard nonparametric prior processes.

    We propose an analysis of prior choices associated by their property of conservativeness in the number of components. Among the proposals, we derive a prior distribution on the number of clusters which considers the loss one would incur if the true value representing the number of components were not considered. The prior has an elegant and easy to implement structure, which allows to naturally include any prior information one may have as well as to opt for a default solution in cases where this information is not available.

    The methods are then applied on two real data-sets. The first data-set consists of retrieval times for monitoring IP packets in computer network systems. The second data-set consists of measures registered in antimicrobial susceptibility tests for 14 compounds used in the treatment of M. Tuberculosis.  In both the situations, the number of clusters is uncertain and different solutions lead to different interpretations. 

    Biography: Dr Clara Grazian received a joint PhD in 2016 from Université Paris-Dauphine under the supervision of Prof. Christian Robert and from Sapienza Università di Roma under the supervision of Prof. Brunero Liseo. She is currently Senior Lecturer in the School of Mathematics and Statistics at UNSW.

    Her research interests include: Bayesian statistics, mixture models, spatio-temporal modelling and copula models and variable selection, with applications in climatology, epidemiology, cybersecurity and genetics. 

    Before joining UNSW, she was Postdoctoral Fellow at the University of Oxford, working on understanding genomic mechanisms conferring resistance to tuberculosis. Her research focuses on methodological aspects of statistics, as well as applied problems, where she uses tools from both statistics and machine learning to assure consistency andtheoretical properties together with computational efficiency.

    Zoom link:

    You are invited to a Zoom meeting.
    When: Mar 1, 2022 05:30 PM Canberra, Melbourne, Sydney

    The start time is 5:30pm to allow 15mins pre-mingling. Registration is required for the meeting


    Register in advance for this meeting:

    After registering, you will receive a confirmation email containing information about joining the meeting.


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