Mixture models : Theory and applications

Session

Mixture modelling and applications

21 juin 2018, 14:00

Amphi Risler (jeudi), Amphi Tisserand (vendredi) (Paris)

6. Variable selection for latent class analysis with application to low back pain diagnosis

Prof. Brendan Murphy (University College Dublin)

21/06/2018 14:00

The identification of most relevant clinical criteria related to low back pain disorders may aid the evaluation of the nature of pain suffered in a way that usefully informs patient assessment and treatment. Data concerning low back pain can be of categorical nature, in the form of a check-list in which each item denotes presence or absence of a clinical condition. Latent class analysis is a...

7. The stochastic topic block model

Dr Pierre Latouche (Université Paris 1)

21/06/2018 15:00

Due to the significant increase of communications between individuals via social media (Facebook, Twitter, Linkedin) or electronic formats (email, web, e-publication) in the past two decades, network analysis has become a unavoidable discipline. Many random graph models have been proposed to extract information from networks based on person-to-person links only, without taking into account...

8. How to use Gaussian mixture models on patches for solving image inverse problems

M. Antoine Houdard (Télécom ParisTech / MAP5)

21/06/2018 16:00

Most patch-based methods used in image processing involve Gaussian models or Gaussian mixture models. All theses methods can be seen through the same statistical framework. The most challenging part is the parameters estimation in the high dimensional patches space. After a brief introduction on image restoration, I will present the High-Dimensional Mixture model we introduced for image...

9. Issues, Challenges and Models for Document Clustering

Prof. Mohamed Nadif (LIPADE / University of Paris Descartes)

21/06/2018 16:30

In recent years, document clustering or text clustering techniques have been receiving more and more attentions as a fundamental and efficient tool for organization and summarization of huge volumes of text documents. In this talk, I provide a detailed survey of the problem of document clustering. I discuss a number of recent advances in this area and in the clustering and co-clustering...